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Applied Research – Types, Methods and Examples

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Applied Research

Definition:

Applied research is a type of scientific inquiry that focuses on developing practical solutions to real-world problems. It involves the use of existing knowledge, theories, and techniques to address specific problems or challenges in a particular field or industry.

Applied research is often conducted in collaboration with industry or government partners, who provide funding and expertise to support the research. The results of applied research are typically intended to be directly applicable to the real world, and may involve the development of new products, technologies, or processes.

Types of Applied Research

Types of Applied Research are as follows:

Action Research

This type of research is designed to solve specific problems within an organization or community. The research involves collaboration between researchers and stakeholders to develop solutions to issues that affect the organization or community.

Evaluation Research

This type of research is used to assess the effectiveness of a particular program, policy, or intervention. Evaluation research is often used in government, healthcare, and social service settings to determine whether programs are meeting their intended goals.

Developmental Research

This type of research is used to develop new products, technologies, or processes. The research may involve the testing of prototypes or the development of new methods for production or delivery.

Diagnostic Research

This type of research is used to identify the causes of problems or issues. Diagnostic research is often used in healthcare, where researchers may investigate the causes of a particular disease or condition.

Policy Research

This type of research is used to inform policy decisions. Policy research may involve analyzing the impact of existing policies or evaluating the potential outcomes of proposed policies.

Predictive Research

This type of research is used to forecast future trends or events. Predictive research is often used in marketing, where researchers may use data analysis to predict consumer behavior or market trends.

Data Collection Methods

In applied research, data collection methods can be broadly classified into two categories: Quantitative and Qualitative methods:

Quantitative Data Collection

Quantitative research methods involve collecting numerical data that can be analyzed statistically. The most commonly used quantitative data collection methods in applied research include:

• Surveys : Surveys are questionnaires designed to collect data from a large sample of people. Surveys can be conducted face-to-face, over the phone, or online.
• Experiments : Experiments involve manipulating variables to test cause-and-effect relationships. Experiments can be conducted in the lab or in the field.
• Observations : Observations involve watching and recording behaviors or events in a systematic way. Observations can be conducted in the lab or in natural settings.
• Secondary data analysis: Secondary data analysis involves analyzing data that has already been collected by someone else. This can include data from government agencies, research institutes, or other sources.

Qualitative Data Collection

Qualitative research methods involve collecting non-numerical data that can be analyzed for themes and patterns. The most commonly used qualitative data collection methods in applied research include:

• Interviews : Interviews involve asking open-ended questions to individuals or groups. Interviews can be conducted in-person, over the phone, or online.
• Focus groups : Focus groups involve a group of people discussing a topic with a moderator. Focus groups can be conducted in-person or online.
• Case studies : Case studies involve in-depth analysis of a single individual, group, or organization.
• Document analysis : Document analysis involves analyzing written or recorded documents to extract data. This can include analyzing written records, audio recordings, or video recordings.

Data Analysis Methods

In applied research, data analysis methods can be broadly classified into two categories: Quantitative and Qualitative methods:

Quantitative Data Analysis

Quantitative data analysis methods involve analyzing numerical data to identify patterns and trends. The most commonly used quantitative data analysis methods in applied research include:

• Descriptive statistics: Descriptive statistics involve summarizing and presenting data using measures such as mean, median, mode, and standard deviation.
• Inferential statistics : Inferential statistics involve testing hypotheses and making predictions about a population based on a sample of data. This includes methods such as t-tests, ANOVA, regression analysis, and correlation analysis.
• Data mining: Data mining involves analyzing large datasets to identify patterns and relationships using machine learning algorithms.

Qualitative Data Analysis

Qualitative data analysis methods involve analyzing non-numerical data to identify themes and patterns. The most commonly used qualitative data analysis methods in applied research include:

• Content analysis: Content analysis involves analyzing written or recorded data to identify themes and patterns. This includes methods such as thematic analysis, discourse analysis, and narrative analysis.
• Grounded theory: Grounded theory involves developing theories and hypotheses based on the analysis of data.
• Interpretative phenomenological analysis: Interpretative phenomenological analysis involves analyzing data to identify the subjective experiences of individuals.
• Case study analysis: Case study analysis involves analyzing a single individual, group, or organization in-depth to identify patterns and themes.

Applied Research Methodology

Applied research methodology refers to the set of procedures, tools, and techniques used to design, conduct, and analyze research studies aimed at solving practical problems in real-world settings. The general steps involved in applied research methodology include:

• Identifying the research problem: The first step in applied research is to identify the problem to be studied. This involves conducting a literature review to identify existing knowledge and gaps in the literature, and to determine the research question.
• Developing a research design : Once the research question has been identified, the next step is to develop a research design. This involves determining the appropriate research method (quantitative, qualitative, or mixed methods), selecting the data collection methods, and designing the sampling strategy.
• Collecting data: The third step in applied research is to collect data using the selected data collection methods. This can include surveys, interviews, experiments, observations, or a combination of methods.
• Analyzing data : Once the data has been collected, it needs to be analyzed using appropriate data analysis methods. This can include descriptive statistics, inferential statistics, content analysis, or other methods, depending on the type of data collected.
• Interpreting and reporting findings : The final step in applied research is to interpret the findings and report the results. This involves drawing conclusions from the data analysis and presenting the findings in a clear and concise manner.

Applications of Applied Research

Some applications of applied research are as follows:

• Product development: Applied research can help companies develop new products or improve existing ones. For example, a company might conduct research to develop a new type of battery that lasts longer or a new type of software that is more efficient.
• Medical research : Applied research can be used to develop new treatments or drugs for diseases. For example, a pharmaceutical company might conduct research to develop a new cancer treatment.
• Environmental research : Applied research can be used to study and address environmental problems such as pollution and climate change. For example, research might be conducted to develop new technologies for reducing greenhouse gas emissions.
• Agriculture : Applied research can be used to improve crop yields, develop new varieties of plants, and study the impact of pests and diseases on crops.
• Education : Applied research can be used to study the effectiveness of teaching methods or to develop new teaching strategies.
• Transportation : Applied research can be used to develop new technologies for transportation, such as electric cars or high-speed trains.
• Communication : Applied research can be used to improve communication technologies, such as developing new methods for wireless communication or improving the quality of video calls.

Examples of Applied Research

Here are some real-time examples of applied research:

• COVID-19 Vaccine Development: The development of COVID-19 vaccines is a prime example of applied research. Researchers applied their knowledge of virology and immunology to develop vaccines that could prevent or reduce the severity of COVID-19.
• Autonomous Vehicles : The development of autonomous vehicles involves applied research in areas such as artificial intelligence, computer vision, and robotics. Companies like Tesla, Waymo, and Uber are conducting extensive research to improve their autonomous vehicle technology.
• Renewable Energy : Research is being conducted on renewable energy sources like solar, wind, and hydro power to improve efficiency and reduce costs. This is an example of applied research that aims to solve environmental problems.
• Precision Agriculture : Applied research is being conducted in the field of precision agriculture, which involves using technology to optimize crop yields and reduce waste. This includes research on crop sensors, drones, and data analysis.
• Telemedicine : Telemedicine involves using technology to deliver healthcare remotely. Applied research is being conducted to improve the quality of telemedicine services, such as developing new technologies for remote diagnosis and treatment.
• Cybersecurity : Applied research is being conducted to improve cybersecurity measures and protect against cyber threats. This includes research on encryption, network security, and data protection.

Purpose of Applied Research

The purpose of applied research is to solve practical problems or improve existing products, technologies, or processes. Applied research is focused on specific goals and objectives and is designed to have direct practical applications in the real world. It seeks to address problems and challenges faced by individuals, organizations, or communities and aims to provide solutions that can be implemented in a practical manner.

The primary purpose of applied research is to generate new knowledge that can be used to solve real-world problems or improve the efficiency and effectiveness of existing products, technologies, or processes. Applied research is often conducted in collaboration with industry, government, or non-profit organizations to address practical problems and create innovative solutions.

Applied research is also used to inform policy decisions by providing evidence-based insights into the effectiveness of specific interventions or programs. By conducting research on the impact of policies and programs, decision-makers can make informed decisions about how to allocate resources and prioritize interventions.

Overall, the purpose of applied research is to improve people’s lives by developing practical solutions to real-world problems. It aims to bridge the gap between theory and practice, and to ensure that research findings are put into action to achieve tangible benefits.

When to use Applied Research

Here are some specific situations when applied research may be appropriate:

• When there is a need to develop a new product : Applied research can be used to develop new products that meet the needs of consumers. For example, a company may conduct research to develop a new type of smartphone with improved features.
• When there is a need to improve an existing product : Applied research can also be used to improve existing products. For example, a company may conduct research to improve the battery life of an existing product.
• When there is a need to solve a practical problem: Applied research can be used to solve practical problems faced by individuals, organizations, or communities. For example, research may be conducted to find solutions to problems related to healthcare, transportation, or environmental issues.
• When there is a need to inform policy decisions: Applied research can be used to inform policy decisions by providing evidence-based insights into the effectiveness of specific interventions or programs.
• When there is a need to improve efficiency and effectiveness: Applied research can be used to improve the efficiency and effectiveness of processes or systems. For example, research may be conducted to identify ways to streamline manufacturing processes or to improve the delivery of healthcare services.

Characteristics of Applied Research

The following are some of the characteristics of applied research:

• Focus on solving real-world problems : Applied research focuses on addressing specific problems or needs in a practical setting, with the aim of developing solutions that can be implemented in the real world.
• Goal-oriented: A pplied research is goal-oriented, with a specific aim of solving a particular problem or meeting a specific need. The research is usually designed to achieve a specific outcome, such as developing a new product, improving an existing process, or solving a particular issue.
• Practical and relevant: Applied research is practical and relevant to the needs of the industry or field in which it is conducted. It aims to provide practical solutions that can be implemented to improve processes or solve problems.
• Collaborative : Applied research often involves collaboration between researchers and practitioners, such as engineers, scientists, and business professionals. Collaboration allows for the exchange of knowledge and expertise, which can lead to more effective solutions.
• Data-driven: Applied research is data-driven, relying on empirical evidence to support its findings and recommendations. Data collection and analysis are important components of applied research, as they help to identify patterns and trends that can inform decision-making.
• Results-oriented: Applied research is results-oriented, with an emphasis on achieving measurable outcomes. Research findings are often used to inform decisions about product development, process improvement, or policy changes.
• Time-bound : Applied research is often conducted within a specific timeframe, with deadlines for achieving specific outcomes. This helps to ensure that the research stays focused on its goals and that the results are timely and relevant to the needs of the industry or field.

Advantages of Applied Research

Some of the advantages of applied research are as follows:

• Practical solutions: Applied research is focused on developing practical solutions to real-world problems, making it highly relevant to the needs of the industry or field in which it is conducted. The solutions developed through applied research are often highly effective and can be implemented quickly to address specific issues.
• Improved processes: Applied research can help organizations to improve their processes, leading to increased efficiency and productivity. The research can identify areas for improvement, such as bottlenecks or inefficiencies, and provide recommendations for optimizing processes.
• Innovation: Applied research can lead to the development of new products, services, and technologies that can transform industries and create new opportunities for growth and innovation. The research can help organizations to identify unmet needs and develop new solutions to meet them.
• Collaboration : Applied research often involves collaboration between researchers and practitioners, leading to the exchange of knowledge and expertise. Collaboration can result in more effective solutions and can help to build partnerships between academia and industry.
• Increased competitiveness : Applied research can help organizations to stay competitive by enabling them to adapt to changing market conditions and customer needs. The research can provide insights into emerging trends and technologies, helping organizations to stay ahead of the curve.
• Economic growth: Applied research can contribute to economic growth by creating new industries and jobs. The research can lead to the development of new technologies and products that can drive economic growth and create new opportunities for entrepreneurship and innovation.

Limitations of Applied Research

Some of the limitations of applied research are as follows:

• Limited generalizability: Applied research often focuses on specific contexts and may not be generalizable to other settings. This means that the findings of applied research may not be applicable to other industries, regions, or populations.
• Time and resource constraints: Applied research is often conducted within a specific timeframe and with limited resources. This can limit the scope and depth of the research and may prevent researchers from exploring all possible avenues.
• Potential for bias: Applied research may be influenced by the interests and perspectives of the organization or industry funding the research. This can lead to a bias in the research and potentially compromise the objectivity and validity of the findings.
• Ethical considerations: Applied research may raise ethical concerns, particularly if it involves human subjects or sensitive issues. Researchers must adhere to ethical standards and ensure that the research is conducted in a responsible and respectful manner.
• Limited theoretical development: Applied research tends to focus on practical solutions and may not contribute significantly to theoretical development in a particular field. This can limit the broader impact of the research and may hinder the development of new theories and frameworks.
• Limited focus on long-term impact: Applied research often focuses on short-term outcomes, such as developing a new product or improving a process. This may limit the focus on long-term impacts, such as the sustainability of the solution or its broader implications for the industry or society.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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What is Applied Research? Definition, Types, Examples

Appinio Research · 10.01.2024 · 35min read

Ever wondered how groundbreaking solutions to real-world challenges are developed, or how innovations come to life? Applied research holds the key. In this guide, we will delve deep into the world of applied research, uncovering its principles, methodologies, and real-world impact.  From harnessing cutting-edge technology to address healthcare crises to revolutionizing industries through data-driven insights, we'll explore the diverse domains where applied research thrives.

What is Applied Research?

Applied research is a systematic and organized inquiry aimed at solving specific real-world problems or improving existing practices, products, or services. Unlike basic research, which focuses on expanding general knowledge, applied research is all about using existing knowledge to address practical issues.

The primary purpose of applied research is to generate actionable insights and solutions that have a direct impact on practical situations. It seeks to bridge the gap between theory and practice by taking existing knowledge and applying it in real-world contexts. Applied research is driven by the need to address specific challenges, make informed decisions, and drive innovation in various domains.

Importance of Applied Research

Applied research holds immense significance across various fields and industries. Here's a list of reasons why applied research is crucial:

• Problem Solving:  Applied research provides effective solutions to real-world problems, improving processes, products, and services.
• Innovation:  It drives innovation by identifying opportunities for enhancement and developing practical solutions.
• Evidence-Based Decision-Making:  Policymakers and decision-makers rely on applied research findings to make informed choices and shape effective policies.
• Competitive Advantage:  In business, applied research can lead to improved products, increased efficiency, and a competitive edge in the market.
• Social Impact:  Applied research contributes to solving societal issues, from healthcare improvements to environmental sustainability.
• Technological Advancement:  In technology and engineering, it fuels advancements by applying scientific knowledge to practical applications.

Applied Research vs. Basic Research

Applied research differs from basic research in several key ways:

• Objectives:  Applied research aims to address specific practical problems or improve existing processes, while basic research seeks to expand general knowledge.
• Focus:  Applied research focuses on solving real-world challenges, whereas basic research explores fundamental principles and concepts.
• Applicability:  Applied research findings are directly applicable to practical situations, while basic research often lacks immediate practical applications.
• Immediate Impact:  Applied research has a more immediate impact on solving problems and improving practices, whereas basic research may have longer-term or indirect effects on knowledge and innovation.
• Research Questions:  Applied research formulates research questions related to practical issues, while basic research poses questions to explore theoretical or fundamental concepts.

Understanding these distinctions is essential for researchers, policymakers, and stakeholders in various fields, as it guides the choice of research approach and the expected outcomes of a research endeavor.

Types of Applied Research

Applied research encompasses various types, each tailored to specific objectives and domains. Understanding these types is essential for choosing the right approach to address real-world problems effectively. Here are some common types of applied research, each with its distinct focus and methodologies.

Evaluation Research

Purpose:  Evaluation research assesses the effectiveness, efficiency, and impact of programs, interventions, or policies. It aims to determine whether these initiatives meet their intended goals and objectives.

Methodology:  Researchers employ a range of quantitative and qualitative methods , including surveys, interviews, observations, and data analysis, to evaluate the outcomes and outcomes of programs or interventions.

Example:  Evaluating the impact of a public health campaign aimed at reducing smoking rates by analyzing pre- and post-campaign survey data on smoking habits and attitudes.

Action Research

Purpose:  Action research focuses on solving practical problems within a specific organizational or community context. It involves collaboration between researchers and practitioners to implement and assess solutions.

Methodology:  Action research is iterative and participatory, with researchers and stakeholders working together to identify problems, develop interventions, and assess their effectiveness. It often involves cycles of planning, action, reflection, and adjustment.

Example:  Teachers collaborating with researchers to improve classroom teaching methods and student outcomes by implementing and refining innovative teaching strategies.

Case Study Research

Purpose:   Case study research investigates a particular individual, organization, or situation in-depth to gain a comprehensive understanding of a specific phenomenon or issue.

Methodology:  Researchers collect and analyze a wealth of data, which may include interviews, documents, observations, and archival records. The goal is to provide a detailed and context-rich description of the case.

Example:  A detailed examination of a successful startup company's growth strategies and challenges, offering insights into factors contributing to its success.

Applied Experimental Research

Purpose:  Applied experimental research seeks to establish causal relationships between variables by manipulating one or more factors and observing their impact on outcomes. It helps determine cause-and-effect relationships in real-world settings.

Methodology:  Researchers conduct controlled experiments, similar to those in basic research, but within practical contexts. They manipulate variables and use statistical analysis to assess their effects on specific outcomes.

Example:  Testing the impact of different website designs on user engagement and conversion rates by randomly assigning visitors to various design versions and measuring their interactions.

Survey Research

Purpose:   Survey research involves collecting data from a sample of individuals or organizations to understand their opinions, attitudes, behaviors, or characteristics. It is commonly used to gather quantitative data on specific topics.

Methodology:  Researchers design surveys with carefully crafted questions and administer them to a representative sample of the target population . Statistical analysis is used to draw conclusions based on survey responses.

Example:  Conducting a national survey to assess public sentiment and preferences on environmental conservation initiatives and policies.

These types of applied research provide a framework for approaching real-world challenges systematically. Researchers can choose the most appropriate type based on their research goals, objectives, and the nature of the problem or phenomenon they seek to address. By selecting the right approach, applied researchers can generate valuable insights and practical solutions in various fields and disciplines.

How to Prepare for Applied Research?

In the preparatory phase of your applied research journey, you'll lay the groundwork for a successful study. This phase involves a series of crucial steps that will shape the direction and ethics of your research project.

Identifying Research Questions

One of the key starting points for any applied research endeavor is identifying the right research questions. Your research questions should be clear, specific, and directly related to the problem or issue you aim to address.

• Engage with Stakeholders:  Reach out to individuals or groups who are affected by or have an interest in the issue you're researching. Their perspectives can help you formulate relevant questions.
• Consider Feasibility:  Ensure that your research questions are feasible within your available resources, including time, budget, and access to data or participants.
• Prioritize Impact:  Focus on questions that have the potential to create meaningful change or provide valuable insights in your chosen field.

Formulating Hypotheses

Hypotheses serve as the guiding stars of your research, providing a clear direction for your investigation. Formulating hypotheses is a critical step that sets the stage for testing and validating your ideas.

• Testable Predictions:  Your hypotheses should be testable and capable of being proven or disproven through empirical research.
• Informed by Literature:  Base your hypotheses on existing knowledge and insights gained from the literature review. They should build upon what is already known and aim to expand that knowledge.
• Clarity and Precision:  Write your hypotheses in a clear and precise manner, specifying the expected relationship or outcome you intend to explore.

Literature Review

Conducting a thorough literature review is like embarking on a treasure hunt through existing knowledge in your field. It's a comprehensive exploration of what other researchers have already discovered and what gaps in knowledge still exist.

• Search Strategies:  Utilize academic databases, journals, books, and credible online sources to search for relevant literature.
• Analyze Existing Research:  Examine the findings, methodologies, and conclusions of previous studies related to your research topic.
• Identify Research Gaps:  Look for areas where current knowledge is insufficient or contradictory. These gaps will be the foundation for your own research.

Data Collection Methods

Selecting the proper data collection methods is crucial to gather the information needed to address your research questions. The choice of methods will depend on the nature of your research and the type of data you require.

• Quantitative vs. Qualitative:  Decide whether you will collect numerical data (quantitative) or focus on descriptive insights and narratives (qualitative).
• Survey Design :  If surveys are part of your data collection plan, carefully design questions that are clear, unbiased, and aligned with your research goals.
• Sampling Strategies:  Determine how you will select participants or data points to ensure representativeness and reliability.

Ethical Considerations

Ethical considerations are at the heart of responsible research. Ensuring that your study is conducted ethically and with integrity is paramount.

• Informed Consent:  Obtain informed consent from participants, ensuring they understand the purpose of the research, potential risks, and their right to withdraw at any time.
• Confidentiality:  Safeguard participants' personal information and ensure their anonymity when reporting findings.
• Minimizing Harm:  Take measures to mitigate any physical or emotional harm that participants may experience during the research process.
• Ethical Reporting:  Accurately represent your research findings, avoiding manipulation or selective reporting that may mislead readers or stakeholders.

By diligently addressing these aspects of research preparation, you are building a solid foundation for your applied research project, setting the stage for effective data collection and meaningful analysis in the subsequent phases of your study.

How to Design Your Research Study?

When it comes to applied research, the design of your study is paramount. It shapes the entire research process, from data collection to analysis and interpretation. In this section, we will explore the various elements that make up the foundation of your research design.

Research Design Types

Your choice of research design is like selecting the blueprint for your research project. Different research design types offer unique advantages and are suited for different research questions. Here are some common research design types:

• Experimental Design :  In this design, researchers manipulate one or more variables to observe their impact on outcomes. It allows for causal inference but may not always be feasible in applied research due to ethical or practical constraints.
• Descriptive Design:  This design aims to describe a phenomenon or population without manipulating variables. It is often used when researchers want to provide a snapshot of a situation or gain insights into a specific context.
• Correlational Design :  In this design, researchers examine relationships between variables without manipulating them. It helps identify associations but does not establish causation.
• Longitudinal Design :   Longitudinal studies involve collecting data from the same subjects over an extended period. They are valuable for tracking changes or developments over time.
• Cross-Sectional Design :  This design involves data collection from a diverse group of subjects at a single point in time. It's helpful in studying differences or variations among groups.

Sampling Methods

Sampling methods determine who or what will be included in your study. The choice of sampling method has a significant impact on the generalizability of your findings. Here are some standard sampling methods:

• Random Sampling:  This method involves selecting participants or data points entirely at random from the population. It ensures every element has an equal chance of being included, which enhances representativeness .
• Stratified Sampling:  In stratified sampling, the population is divided into subgroups or strata, and then random samples are drawn from each stratum. This method ensures that each subgroup is adequately represented.
• Convenience Sampling:  Researchers choose subjects or data points that are readily available and accessible. While convenient, this method may lead to sampling bias as it may not accurately represent the entire population.
• Purposive Sampling:  In purposive sampling, researchers deliberately select specific individuals or groups based on their expertise, experience, or relevance to the research topic. It is often used when seeking specialized knowledge.

Data Collection Tools

Selecting the right data collection tools is essential to gather accurate and relevant information. Your choice of tools will depend on the research design and objectives. Standard data collection tools include:

• Questionnaires and Surveys:  These structured instruments use standardized questions to gather data from participants. They are suitable for collecting large amounts of quantitative data.
• Interviews:   Interviews can be structured, semi-structured, or unstructured. They provide an opportunity to gather in-depth, qualitative insights from participants.
• Observation:  Direct observation involves systematically watching and recording behaviors or events. It's valuable for studying behaviors or phenomena in their natural context.
• Secondary Data :  Researchers can also utilize existing data sources, such as government reports, databases, or historical records, for their research.

Variables and Measurement

Defining variables and choosing appropriate measurement methods is crucial for ensuring the reliability and validity of your research. Variables are characteristics, phenomena, or factors that can change or vary in your study. They can be categorized into:

• Independent Variables:  These are the variables you manipulate or control in your study to observe their effects on other variables.
• Dependent Variables:  These are the variables you measure to assess the impact of the independent variables.

Choosing the right measurement techniques, scales, or instruments is essential to accurately quantify variables and collect valid data. It's crucial to establish clear operational definitions for each variable to ensure consistency in measurement.

Data Analysis Techniques

Once you have collected your data, the next step is to analyze it effectively. Data analysis involves:

• Data Cleaning:  Removing any errors, inconsistencies, or outliers from your dataset to ensure data quality.
• Statistical Analysis :  Depending on your research design and data type, you may use various statistical techniques such as regression analysis , t-tests, ANOVA, or chi-square tests.
• Qualitative Analysis:  For qualitative data, techniques like thematic analysis, content analysis, or discourse analysis help uncover patterns and themes.
• Data Visualization:  Using graphs, charts, and visual representations to present your data effectively.

Chi-Square Calculator :

t-Test Calculator :

One-way ANOVA Calculator :

Selecting the appropriate analysis techniques depends on your research questions, data type, and objectives. Proper data analysis is crucial for drawing meaningful conclusions and insights from your research.

With a solid understanding of research design, sampling methods, data collection tools, variables, and measurement, you are well-equipped to embark on your applied research journey. These elements lay the groundwork for collecting valuable data and conducting meaningful analyses in the subsequent phases of your study.

How to Conduct Applied Research?

Now that you've prepared and designed your research study, it's time to delve into the practical aspects of conducting applied research. This phase involves the execution of your research plan, from collecting data to drawing meaningful conclusions. Let's explore the critical components in this stage.

Data Collection Phase

The data collection phase is where your research plan comes to life. It's a crucial step that requires precision and attention to detail to ensure the quality and reliability of your data.

• Implement Data Collection Methods:   Execute the data collection methods you've chosen, whether they involve surveys, interviews, observations, or the analysis of existing datasets.
• Maintain Consistency:  Ensure that data collection is carried out consistently according to your research design and protocols. Minimize any variations or deviations that may introduce bias .
• Document the Process:  Keep thorough records of the data collection process. Note any challenges, unexpected occurrences, or deviations from your original plan. Documentation is essential for transparency and replication.
• Quality Assurance:  Continuously monitor the quality of the data you collect. Check for errors, missing information, or outliers. Implement data validation and cleaning procedures to address any issues promptly.
• Participant Engagement:  If your research involves human participants, maintain open and respectful communication with them. Address any questions or concerns and ensure participants' comfort and willingness to participate.

Data Analysis Phase

Once you've collected your data, it's time to make sense of the information you've gathered. The data analysis phase involves transforming raw data into meaningful insights and patterns.

• Data Preparation:  Start by organizing and cleaning your data. This includes dealing with missing values, outliers, and ensuring data consistency.
• Selecting Analysis Methods:  Depending on your research design and data type, choose the appropriate statistical or qualitative analysis methods. Common techniques include regression analysis , content analysis, or thematic coding .
• Conducting Analysis:  Perform the chosen analysis systematically and according to established protocols. Ensure that your analysis is reproducible by documenting every step.
• Interpreting Results:  Interpretation involves making sense of your findings in the context of your research questions and hypotheses. Consider the statistical significance of the results and any practical implications they may have.
• Visualization:  Create visual representations of your data, such as graphs, charts, or tables, to convey your findings effectively. Visualizations make complex data more accessible to a broader audience.

Interpretation of Results

Interpreting research results is a critical step that bridges the gap between data analysis and drawing conclusions. This process involves making sense of the patterns and insights that emerge from your analysis.

• Relate to Hypotheses:  Determine whether your results support or refute your hypotheses. Be prepared to explain any unexpected findings.
• Contextualize Findings:  Consider the broader context in which your research takes place. How do your results fit into the larger body of knowledge in your field?
• Identify Patterns :  Highlight significant trends, correlations, or relationships you've uncovered. Discuss their practical implications and relevance.
• Acknowledge Limitations:  Be transparent about any limitations in your study that may affect the interpretation of results. This includes sample size, data quality, and potential biases.

Drawing Conclusions

Drawing conclusions is the ultimate goal of your research. It involves synthesizing your findings and answering the research questions you initially posed.

• Answer Research Questions:  Explicitly address the research questions you formulated at the beginning of your study. State whether your findings confirm or challenge your initial hypotheses.
• Highlight Insights:  Emphasize the key insights and contributions of your research. Discuss the practical implications of your findings and their relevance to the field.
• Recommend Actions:  Based on your conclusions, suggest practical steps, recommendations, or future research directions. How can your research contribute to addressing the problem or challenge you investigated?
• Consider Implications:  Reflect on the broader implications of your research for stakeholders, policymakers, or practitioners in your field.

Common Pitfalls to Avoid

During the data collection, analysis, interpretation, and conclusion-drawing phases, it's essential to be aware of common pitfalls that can affect the quality and integrity of your research.

• Sampling Bias :  Ensure that your sample is representative of the population you intend to study. Address any bias that may have been introduced during data collection.
• Data Manipulation:  Avoid manipulating or selectively reporting data to fit preconceived notions. Maintain transparency in your analysis and reporting.
• Overinterpretation:  Be cautious of drawing overly broad conclusions based on limited data. Acknowledge the limitations of your study.
• Ignoring Ethical Considerations:  Continuously uphold ethical standards in your research, from data collection to reporting. Protect participants' rights and privacy.
• Lack of Validation:  Ensure that the methods and tools you use for data collection and analysis are valid and reliable. Validation helps establish the credibility of your findings.

By navigating the data collection, analysis, interpretation, and conclusion-drawing phases with care and attention to detail, you'll be well-prepared to confidently share your research findings and contribute to advancing knowledge in your field.

How to Report Applied Research Results?

Now that you've conducted your applied research and drawn meaningful conclusions, it's time to share your insights with the world. Effective reporting and communication are crucial to ensure that your research has a real impact and contributes to the broader knowledge base.

Writing Research Reports

Writing a comprehensive research report is the cornerstone of communicating your findings. It provides a detailed account of your research process, results, and conclusions. Here's what you need to consider:

Structure of a Research Report

• Title:  Create a concise, informative title that reflects the essence of your research.
• Abstract:  Summarize your research in a clear and concise manner, highlighting key objectives, methods, results, and conclusions.
• Introduction:  Provide an overview of your research topic, objectives, significance, and research questions.
• Literature Review:  Summarize relevant literature and identify gaps in existing knowledge that your research addresses.
• Methodology:  Describe your research design, sampling methods, data collection tools, and data analysis techniques.
• Results:  Present your findings using tables, charts, and narratives. Be transparent and objective in reporting your results.
• Discussion:  Interpret your results, discuss their implications, and relate them to your research questions and hypotheses.
• Conclusion:  Summarize your main findings, their significance, and the implications for future research or practical applications.
• References:  Cite all sources and studies you referenced in your report using a consistent citation style (e.g., APA, MLA).

Writing Tips

• Use clear and concise language, avoiding jargon or overly technical terms.
• Organize your report logically, with headings and subheadings for easy navigation.
• Provide evidence and data to support your claims and conclusions.
• Consider your target audience and tailor the report to their level of expertise and interest.

Creating Visualizations

Visualizations are powerful tools for conveying complex data and making your research findings more accessible. Here are some types of visualizations commonly used in research reports:

Charts and Graphs

• Bar Charts:  Ideal for comparing categories or groups.
• Line Charts:  Effective for showing trends or changes over time.
• Pie Charts:  Useful for displaying proportions or percentages.
• Data Tables:  Present numerical data in an organized format.
• Cross-tabulations:  Show relationships between variables.

Diagrams and Maps

• Flowcharts:  Visualize processes or workflows.
• Concept Maps:  Illustrate connections between concepts.
• Geographic Maps:  Display spatial data and patterns.

When creating visualizations:

• Choose the correct type of visualization for your data and research questions.
• Ensure that visualizations are labeled, clear, and easy to understand.
• Provide context and explanations to help readers interpret the visuals.

Presenting Your Research

Presenting your research to an audience is an opportunity to engage, educate, and inspire. Whether it's through a conference presentation, seminar, or webinar, effective communication is vital.

• Know Your Audience:  Tailor your presentation to the interests and expertise of your audience.
• Practice:  Rehearse your presentation to ensure a smooth delivery and confident demeanor.
• Use Visual Aids:  Enhance your presentation with visual aids such as slides, images, or videos.
• Engage with Questions:  Encourage questions and discussions to foster interaction and clarify points.
• Stay within Time Limits:  Respect time constraints and stay on schedule.

Peer Review Process

Before your research is published, it typically undergoes a peer review process. This involves experts in your field evaluating the quality, validity, and significance of your work. The peer review process aims to ensure the integrity and credibility of your research.

• Submission:  Submit your research manuscript to a journal or conference for review.
• Editorial Review:  The editorial team assesses your submission's fit with the journal's scope and may conduct an initial review for quality and compliance.
• Peer Review:  Your manuscript is sent to peer reviewers who evaluate it for methodology, validity, significance, and adherence to ethical standards.
• Feedback and Revision:  Based on reviewers' feedback, you may be asked to revise and improve your research.
• Acceptance or Rejection:  After revisions, the manuscript is reevaluated, and a decision is made regarding publication.

Publishing Your Research

Publishing your research is the final step in sharing your findings with the broader scientific community. It allows others to access and build upon your work. Consider the following when choosing where to publish:

• Journal Selection:  Choose a reputable journal that aligns with your research field and target audience.
• Review Process:  Understand the journal's peer review process and requirements for submission.
• Open Access:  Consider whether you want your research to be open access, freely accessible to all.

Once published, actively promote your research through academic networks, conferences, and social media to maximize its reach and impact.

By effectively reporting and communicating your research findings, you contribute to the advancement of knowledge, inspire others, and ensure that your hard work has a meaningful impact on your field and beyond.

Applied Research Examples

To provide a deeper understanding of applied research's impact and relevance, let's delve into specific real-world examples that demonstrate how this type of research has addressed pressing challenges and improved our lives in tangible ways.

Applied Medical Research: mRNA Vaccines

Example:  mRNA (messenger RNA) vaccine technology, exemplified by the COVID-19 vaccines developed by Pfizer-BioNTech and Moderna, is a remarkable achievement in the field of applied medical research.

Applied researchers in this domain utilized mRNA technology to create vaccines that provide immunity against the SARS-CoV-2 virus. Unlike traditional vaccines, which use weakened or inactivated viruses, mRNA vaccines instruct cells to produce a harmless spike protein found on the virus's surface. The immune system then recognizes this protein and mounts a defense, preparing the body to combat the actual virus.

Impact:  The rapid development and deployment of mRNA vaccines during the COVID-19 pandemic have been groundbreaking. They've played a crucial role in controlling the spread of the virus and saving countless lives worldwide. This example underscores how applied research can revolutionize healthcare and respond swiftly to global health crises.

Environmental Science and Applied Research: Ocean Cleanup

Example:  The Ocean Cleanup Project, founded by Boyan Slat, is an ambitious endeavor rooted in applied research to combat plastic pollution in the world's oceans.

This project employs innovative technology, such as large-scale floating barriers and autonomous systems, to collect and remove plastic debris from the ocean. Applied researchers have played a pivotal role in designing, testing, and optimizing these systems to make them efficient and environmentally friendly.

Impact:  The Ocean Cleanup Project is a testament to the power of applied research in addressing pressing environmental challenges. By removing plastic waste from the oceans, it mitigates harm to marine ecosystems and raises awareness about the urgent need for sustainable waste management.

Business and Applied Research: E-commerce Personalization

Example:   E-commerce giants like Amazon and Netflix use applied research to develop sophisticated personalization algorithms that tailor product recommendations and content to individual users.

Applied researchers in data science and machine learning analyze user behavior, preferences, and historical data to create recommendation systems. These algorithms utilize predictive analytics to suggest products, movies, or shows that align with a user's interests.

Impact:  The application of research-driven personalization has transformed the e-commerce and streaming industries. It enhances user experiences, increases customer engagement, and drives sales by presenting customers with products or content they are more likely to enjoy.

Agriculture and Applied Research: Precision Agriculture

Example:  Precision agriculture employs data-driven technology and applied research to optimize farming practices.

Farmers utilize satellite imagery, sensors, and data analytics to monitor crop conditions, soil health, and weather patterns. Applied research guides the development of precision farming techniques, enabling more efficient resource allocation and reducing environmental impact.

Impact:  Precision agriculture increases crop yields, conserves resources (such as water and fertilizer), and minimizes the ecological footprint of farming. This approach contributes to sustainable and economically viable agriculture.

These real-world examples underscore the versatility and impact of applied research across diverse domains. From healthcare and environmental conservation to business, education, and agriculture, applied research continually drives innovation, addresses critical challenges, and enhances the quality of life for individuals and communities worldwide.

Conclusion for Applied Research

Applied research is a powerful force for solving real-world problems and driving progress. By applying existing knowledge and innovative thinking, we can address healthcare challenges, protect our environment, improve businesses, enhance education, and revolutionize agriculture. Through this guide, you've gained valuable insights into the what, why, and how of applied research, unlocking the potential to make a positive impact in your field. So, go forth, conduct meaningful research, and be part of the solution to the world's most pressing issues. Remember, applied research is not just a concept; it's a practical approach that empowers individuals and teams to create solutions that matter. As you embark on your own applied research endeavors, keep the spirit of inquiry alive, remain open to new ideas, and never underestimate the transformative power of knowledge put into action.

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Applied Research

Applied research “aims at finding a solution for an immediate problem facing a society, or an industrial/business organisation, whereas fundamental research is mainly concerned with generalisations and with the formulation of a theory” [1] . Applied research is considered to be non-systematic inquiry and it is usually launched by a company, agency or an individual in order to address a specific problem. [2]

   Applied research can be divided into the following three categories:

1. Evaluation research . This type of research focuses on analysing existing information about the phenomenon in order to generate objective research outcomes. A study into the ways of reducing supply-chain costs can be mentioned as an example for an evaluation research.

2. Research and Development . It is a type of applied research that focuses on the development of new products and services to satisfy needs and wants of target customer segment. This type of applied research is the least relevant to a business dissertation.

3. Action research . This type of study aims to tackle specific business problems. For example, a research into the ways of restoring Starbucks brand image in UK after the tax scandal can be classified as an action research.

Differences between Applied Research and Fundamental (Basic) Research

The difference between applied and  fundamental or basic research  is straightforward – findings of applied research can be applied to resolve problems, whereas fundamental studies are used simply to explore certain issues and elements. Applied research can be a follow-up to the findings of a fundamental research.

Moreover, differences between applied and basic research can be summarized into three points:

1. Differences in purpose . Purpose of applied studies is closely associated with the solution of specific problems, while the purpose of fundamental studies relate to creation of new knowledge or expansion of the current knowledge without any concerns to applicability.

2. Differences in context . In applied studies, research objectives are set by clients or sponsors as a solution to specific problems they are facing. Fundamental studies, on the other hand, are usually self-initiated in order to expand the levels of knowledge in certain areas.

3. Differences in methods .  Research validity is an important point to be addressed in all types of studies. Nevertheless, applied studies are usually more concerned with external validity, whereas internal validity can be specified as the main point of concern for fundamental researchers.

Examples of Applied Research

The following are examples for applied research. You can notice that each of these studies aim to resolve a specific and an immediate problem.

• A study into marketing strategies to appeal to the aspirations of millenials in China
• An investigation into the ways of improving employee motivation in Marriot Hotel, Hyde Park
• Development of strategies to introduce change in Starbucks global supply-chain management with the view on cost reduction
• A study into the ways of fostering creative deviance amongst employees without compromising respect for authority.

Advantages and Disadvantages of Applied Research

The advantages and disadvantages of applied and fundamental research mirror and contrast each other. On the positive side, applied research can be helpful in solving specific problems in business and other settings.

On the negative side, findings of applied research cannot be usually generalized. In other words, applicability of the new knowledge generated as a result of this type of research is limited to the research problem. Moreover, applied studies usually have tight deadlines which are not flexible.

You need to specify the type of your research in the earlier part of the research methodology chapter in about one short paragraph. Also, in this paragraph you will have to justify your choice of research type.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance   contains discussions of research types and application of research methods in practice. The e-book also explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research approach ,  research design ,  methods of data collection  and  data analysis , sampling and others are explained in this e-book in simple words.

John Dudovskiy

[1] Kothari, C.R. (2008) “Research Methodology: Methods and Techniques” New Age International

[2] Bajpai, N. (2011) “Business Research Methods” Pearson Education India

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Basic vs. applied research: what’s the difference?

Last updated

27 February 2023

Reviewed by

Cathy Heath

Short on time? Get an AI generated summary of this article instead

Research can be used to learn new facts, create new products, and solve various problems. Yet, there are different ways to undertake research to meet a desired goal. 

The method you choose to conduct research will most likely be based on what question you want to answer, plus other factors that will help you accurately get the answer you need. 

Research falls into two main categories: basic research and applied research. Both types of research have distinct purposes and varied benefits. 

This guide will help you understand the differences and similarities between basic and applied research and how they're used. It also answers common questions about the two types of research, including:

Why is it called basic research?

What is more important, basic research or applied research?

What are examples of pure (basic) research and applied research?

Analyze basic and applied research

Dovetail streamlines analysis to help you uncover and share actionable insights

• What is basic research?

Basic research (sometimes called fundamental or pure) advances scientific knowledge to completely understand a subject, topic, or phenomenon. It's conducted to satisfy curiosity or develop a full body of knowledge on a specific subject.

Basic research is used to bring about a fundamental understanding of the world, different behaviors, and is the foundation of knowledge in the scientific disciplines. It is usually conducted based on developing and testing theories.

While there is no apparent commercial value to the discoveries that result from basic research, it is the foundation of research used for other projects like developing solutions to solve problems. 

Examples of basic research

Basic research has always been used to give humans a better understanding of all branches of science and knowledge. However, it's not specifically based on identifying new things about the universe.

Basic research has a wide range of uses, as shown in the following examples:

Investigation into how the universe began

A study searching for the causes of cancer

Understanding the components that make up human DNA

An examination into whether a vegetarian diet is healthier than one with meat

A study to learn more about which areas in the world get the most precipitation

Benefits of conducting basic research

Called basic research because it is performed without an immediate or obvious benefit, this type of research often leads to vital solutions in the future. While basic research isn't technically solution-driven, it develops the underlying knowledge used for additional learning and research. 

There are many benefits derived from basic research, including:

Gaining an understanding of living systems and the environment

Gathering information that can help society prepare for the future

Expanding knowledge that can lead to medical advances

Providing a foundation for applied research

• What is applied research?

Applied research studies particular circumstances to apply the information to real-life situations. It helps improve the human condition by finding practical solutions for existing problems.

Applied research builds off facts derived from basic research and other data to address challenges in all facets of life. Instead of exploring theories of the unknown, applied research requires researchers to use existing knowledge, facts, and discoveries to generate new knowledge. 

Solutions derived from applied research are used in situations ranging from medical treatments or product development to new laws or regulations.

Examples of applied research

Applied research is designed to solve practical problems that exist under current conditions. However, it's not only used for consumer-based products and decisions.

Applied research can be used in a variety of ways, as illustrated by the following examples:

The investigation of ways to improve agricultural crop production

A study to improve methods to market products for Gen Z consumers

Examination of how technology can t make car tires last longer

Exploration of how to cook healthy meals with a limited budget

A study on how to treat patients with insomnia

Benefits of using applied research

Although applied research expands upon a foundation of existing knowledge, it also brings about new ideas. Applied research provides many benefits in various circumstances, including:

Designing new products and services

Creating new objectives

Providing unbiased data through the testing of verifiable evidence

• Basic research vs. applied research: the differences

Both basic and applied research are tactics for discovering specific information. However, they differ significantly in the way research is conducted and the objectives they achieve. 

Some of the most notable differences between basic and applied research include the following:

Research outcomes: curiosity-driven vs. solution-driven

Basic research is generally conducted to learn more about a specific subject. It is usually self-initiated to gain knowledge to satisfy curiosity or confirm a theory. 

Conversely, applied knowledge is directed toward finding a solution to a specific problem. It is often conducted to assist a client in improving products, services, or issues.

Research scope: universal scope vs. specific scope

Basic research uses a broad scope to apply various concepts to gain more knowledge. Research methods may include studying different subjects to add more information that connects evidence points in a greater body of data.

Meanwhile, applied research depends on a specific or narrow scope to gather specific evidence to address a certain problem.

Research approaches: expanding existing knowledge vs. finding new knowledge

Researchers conduct basic research to fill in gaps between existing information points. Basic knowledge is an expansion of existing knowledge to gain a deeper understanding. It is often based on how, what, or why something is the way it is. Although applied research may be based on information derived from basic research, it's not designed to expand the knowledge. Instead, the research is conducted to find new knowledge, usually in the form of a solution.

Research commercialization: Informational vs. commercial gain

The main basis of product development is to solve a problem for consumers.

Basic research might lead to solutions and commercial products in the future to help with this. Since applied research is used to develop solutions, it's often used for commercial gain.

Theory formulation: theoretical vs. practical nature

Basic research is usually based on a theory about a specific subject. Researchers may develop a theory that grows and changes as more information is discovered during the research process. Conversely, applied research is practical in nature since the goal is to solve a specific problem.

• Are there similarities between applied and basic research?

While some obvious differences exist, applied and basic research methods have similarities. For example, researchers may use the same methods to collect data (like interviews, surveys , and focus groups ) for both types of research. 

Both types of research require researchers to use inductive and deductive reasoning to develop and prove hypotheses . The two types of research frequently intersect when basic research serves as the foundation for applied research.

While applied research is solution-based, basic research is equally important because it yields information used to develop solutions to many types of problems. 

• Methods used in basic research and applied research

While basic and applied research have different approaches and goals, they require researchers or scientists to gather data. Basic and applied research makes use of many of the same methods to gather and study information, including the following:

Observations: Studying research subjects for an extended time allows researchers to gather information about how subjects behave under different conditions.

Interviews: Surveys and one-to-one discussions help researchers gain information from other subjects and validate data.

Experiments: Researchers conduct experiments to prove or disprove certain hypotheses based on information that has been gathered.

Questionnaires: A series of questions related to the research context helps researchers gather quantitative information applicable to both basic and applied research.

• How do you determine when to use basic research vs. applied research?

Basic and applied research are both helpful in obtaining knowledge. However, they aren't usually used in the same settings or under the same circumstances. 

When you're trying to determine which type of research to use for a particular project, it's essential to consider your product goals. Basic research seeks answers to universal, theoretical questions. While it works to uncover specific knowledge, it's generally not used to develop a solution. Conversely, applied research discovers answers to specific questions. It should be used to find out new knowledge to solve a problem.

• Bottom line

Both basic and applied research are methods used to gather information and analyze facts that help build knowledge around a subject. However, basic research is used to gain understanding and satisfy curiosity, while applied research is used to solve specific problems. Both types of research depend on gathering information to prove a hypothesis or create a product, service, or valuable process. 

By learning more about the similarities and differences between basic and applied research, you'll be prepared to gather and use data efficiently to meet your needs.

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Basic vs. applied research

• Coding qualitative data for valuable insights

What is the difference between applied research and basic research?

Examples of basic research vs. applied research, basic vs. applied research: a comparative analysis, the interplay between basic and applied research, introduction.

Basic and applied research look at existing knowledge and create new knowledge in different ways. They share the same basic principles of contributing to knowledge through research findings, but their aims and objectives are distinctly different.

In the vast realm of scientific inquiry, research stands as the cornerstone for advancement, driving our understanding of the world and fostering innovation. At its core, research can be bifurcated into two primary types: applied and basic research . While both serve pivotal roles in contributing to our collective knowledge, they operate with distinct objectives and outcomes.

Any approach that is called basic research delves into the foundational principles and theories of science. It is driven by a researcher's curiosity and the aspiration to expand the frontiers of understanding. The primary goal isn't to solve an immediate problem but to garner knowledge for the sake of understanding.

On the other hand, applied research focuses on analysis intended to solve practical problems. Conducting applied research means seeking solutions to specific, tangible challenges that society or industries face. Using the principles derived from basic research, applied research aims to bring about real-world impact and deliver pragmatic solutions.

Basic research

Basic research, often called "pure" or "fundamental" research , is characterized by its intrinsic quest to unravel the mysteries of nature and society. It is an investigation into the very core of phenomena, aiming to discover new principles, theories, or facts without an immediate application in mind. This kind of research is often propelled by the researcher's curiosity, a thirst to understand the "why" and "how" of things, rather than the "what can we do with it."

Basic research has a relatively broad scope and aims to enhance the existing body of knowledge in a particular field. It's not about creating a new product, improving a process, or solving a current societal problem. Instead, it's about laying the groundwork for future investigations, paving the way for applied research to build upon. Basic research poses questions like, "What are the fundamental principles of this phenomenon?" or "How does this process work at different levels?"

Such goals provide the essential framework upon which much of our modern understanding and technological advancement rests. Without the exploratory and explanatory nature of basic research, the foundational knowledge needed to drive innovation would be missing.

Applied research

While basic research focuses on curiosity and the pursuit of knowledge for its own sake, applied research takes a different approach by examining how real-world phenomena or outcomes can be altered. At its core, applied research is oriented towards identifying practical solutions to specific problems. Its primary objective is not just to add to the existing knowledge base but to leverage that knowledge to develop solutions, innovations, or interventions that can be directly applied in the real world.

Applied research is deeply rooted in real-world issues. Whether it's finding a cure for a specific disease, developing a new technological solution for environmental challenges, or creating strategies to improve education in underprivileged communities, the primary goal is to generate practical outcomes that can be directly implemented. Its relevance is often immediately apparent, as it's tailored to answer particular challenges faced by society, industries, or organizations.

The line between basic and applied research can sometimes blur, especially when foundational discoveries from basic research lead directly to tangible applications. However, the main distinction lies in the intent: while basic research seeks to understand the fundamental nature of phenomena, applied research aims to harness that understanding for tangible benefits.

Applied research is invaluable as it accelerates the transition of theoretical knowledge into practical, impactful solutions. Through applied research, the abstract findings of basic research are transformed into actionable insights, tools, and technologies that shape our daily lives and address pressing challenges.

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Research in the social sciences encompasses a broad spectrum of topics, ranging from understanding human behavior and societal structures to exploring the dynamics of interpersonal relationships. Basic and applied research methods in the social sciences offer unique insights into these areas. Let's delve into some examples to understand their distinct approaches.

Basic research examples

The social construction of reality

A classic area of investigation in sociology is understanding how societies construct reality. This kind of research delves deep into the ways cultures, languages, and institutions shape our understanding of the world. It doesn't immediately aim to solve societal problems but provides essential insights into how perceptions and beliefs are formed. Research methods often used for this type of study include in-depth interviews , participant observations , and ethnographic studies .

Attachment theory in psychology

Attachment theory seeks to understand the deep emotional and physical attachment between a child and at least one primary caregiver. It delves into the nature of attachment and its implications for personal development. The research often involves longitudinal studies that observe behaviors over extended periods.

Applied research examples

Interventions for at-risk youth

Applied researchers might design programs or interventions to help at-risk youth, building on the foundational knowledge of psychology, sociology, and education. The research might involve evaluating the effectiveness of a particular program, using methods like surveys , focus groups , and pre-and-post assessments.

Communication strategies for public health

Understanding human behavior is crucial for successful public health campaigns. Researchers might study the best ways to communicate vital health information to various populations, especially in times of crisis like pandemics. Methods often include A/B testing of messages, surveys to assess message efficacy, and observational studies to gauge real-world behavior following communication campaigns.

The distinction between basic and applied research is not just a matter of intent or outcome; it also encompasses differences in methodologies , scopes, and approaches. Let's undertake a comparative analysis to illuminate these distinctions further, particularly in the context of the social sciences.

Purpose and motivation

Basic research is motivated by the quest for knowledge. It seeks to answer fundamental questions about human behavior, societal structures, and the interplay between various social factors. The driving force here is curiosity. In contrast, applied research is driven by the need to address specific societal or practical problems. Its purpose is to take the theoretical knowledge derived from basic research and convert it into actionable solutions.

Methodological approaches

It's important to acknowledge that there is no one universal research method that can address all potential research inquiries. Moreover, the same research methods, such as conducting interviews or engaging in inductive and deductive reasoning , can be utilized in basic and applied research, but they will differ in their scope and objectives. While applied research is more experimental or confirmatory, a basic research approach is often exploratory or explanatory in nature. Basic research methods include ethnography , in-depth interviews , or longitudinal studies to gain a deep understanding of a topic. The focus is on generating theories and understanding patterns.

Applied research, on the other hand, often employs more structured and targeted methodologies. Surveys , experiments, and evaluations are commonly used to verify propositions, assess the efficacy of interventions, or gauge public opinion. The approach is more pragmatic, seeking results that can inform decisions and guide actions.

Outcomes and results

Basic research outcomes are usually theoretical contributions: new concepts, theories, or insights into existing phenomena. The results expand the academic literature and provide a foundation for future studies.

Applied research results in tangible solutions or recommendations. The outcomes might include a new social program, policy recommendations, interventions, or communication strategies. The results are geared towards immediate implementation and often have direct implications for organizations, governments, or communities.

The discourse on basic and applied research often sets them apart, emphasizing their distinct objectives and methodologies. However, it's crucial to recognize that these research types aren't isolated from each other. They coexist in a symbiotic relationship, where the findings from basic research often provide the foundational knowledge for applied research, and the results of applied research can inspire further basic investigations.

The transition of knowledge

One of the most notable instances of the interplay is how basic research's findings become the bedrock for applied research projects. For example, a basic research study on cognitive development in children might reveal specific patterns or stages. An applied researcher, recognizing the implications of these findings, could then design educational interventions tailored to these developmental stages.

How one complements the other

Basic research pushes the boundaries of our understanding, expanding the horizon of what we know. Applied research, on the other hand, can reframe this expansive knowledge and make it relevant and actionable for society's immediate needs.

But the relationship is reciprocal. Applied research can also highlight gaps in our understanding, pointing out areas where basic research is needed. For instance, if an intervention designed based on current knowledge fails to achieve its intended results, it signals to basic researchers that there might be underlying factors or dynamics not yet understood.

The dynamic continuum

Instead of viewing basic and applied research as two separate entities, it's more accurate to see them as points on a continuum. The knowledge generated by basic research flows towards applied projects, which in turn can inspire further basic investigations. This dynamic loop ensures that research in the social sciences remains both grounded in fundamental understanding and relevant to real-world challenges.

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• Translation

Applied Research Essentials: Types, examples, and writing tips

By charlesworth author services.

Commencing a research journey involves a distinct definition of the investigation’s purpose, guiding the selection of the research procedure or approach. In this context, researchers can opt for either basic or applied research , each with its unique characteristics and objectives.

Embarking on the journey of conducting applied research requires a blend of theoretical knowledge and practical application. Understanding the nuances of applied research and its distinctions from basic research is crucial before delving into the intricacies of crafting an impactful paper.

What is Applied Research?

Applied research addresses specific problems with the goal of finding practical solutions. Distinguishing it from basic research, which primarily seeks to expand theoretical knowledge, applied research focuses on resolving real-world issues. It serves as a follow-up to basic or pure research, aiming to identify solutions to specific issues at individual, group, or societal levels.

Applied research encompasses various types, each tailored to address specific challenges and practical issues in different domains. The following are three common types of applied research with examples:

1. Evaluation Research:

• Purpose: Evaluation research aims to assess the effectiveness, efficiency, and relevance of programs, policies, or interventions. It seeks to determine the impact and outcomes of specific actions and initiatives.

• Application: Often employed in business, government, and non-profit sectors, evaluation research helps organisations make informed decisions by providing data-driven insights into the success or shortcomings of their endeavors.

• Example: Evaluating the impact of a workplace training program on employee productivity and job satisfaction.

2. Research and Development (R&D):

• Purpose: Research and Development applied research focuses on creating or enhancing products, goods, or services to meet the needs of specific markets or industries. It involves innovation and design to improve existing offerings or introduce new solutions.

• Application: Commonly found in industries such as technology, pharmaceuticals, and manufacturing, R&D applied research supports the creation of cutting-edge products and processes, contributing to market competitiveness.

• Example: Conducting R&D to develop a new pharmaceutical drug with improved efficacy and fewer side effects.

3. Action Research:

• Purpose: Action research aims to address real-world problems by actively engaging with and observing everyday life and organisational dynamics. It involves a cyclical process of planning, acting, observing, and reflecting to bring about positive change.

• Application: Widely used in fields like education, healthcare, and organisational development, action research empowers practitioners to collaboratively solve problems, improve processes, and enhance outcomes in their specific contexts.

• Example: Implementing action research in a primary school to integrate AI-driven personalised learning platforms. By actively observing the impact of AI on student engagement, understanding, and academic performance, the research aims to refine teaching strategies and optimise the integration of AI in the classroom.

Step-by-Step Guide to Writing an Applied Research Paper

Writing an applied research paper involves a systematic and purposeful approach to address practical issues in a specific field. The following steps provide a comprehensive guide for crafting an effective applied research paper:

1. Selecting a Relevant Topic:

• Identify a specific problem or question within your field of study that requires practical solutions.

• Ensure your topic aligns with the goals of applied research, focusing on real-world issues and challenges.

2. Conducting a Thorough Literature Review:

• Explore existing literature related to your chosen topic to understand the current state of knowledge.

• Identify gaps or areas where applied research can contribute valuable insights.

3. Defining Clear Objectives and Hypotheses:

• Clearly outline the goals and hypotheses of your research to guide the direction of your investigation.

• Ensure that your objectives align with the practical implications you aim to address.

4. Choosing an Appropriate Research Methodology:

• Select a methodology that aligns with your research objectives. This could involve qualitative, quantitative, or mixed methods.

• Justify your choice of methodology and discuss how it will address the practical aspects of your research.

5. Collecting and Analysing Data:

• Implement your chosen methodology to collect relevant data. Ensure that your data collection methods are appropriate for the practical nature of your research.

• Thoroughly analyse the data using appropriate statistical or qualitative analysis techniques.

6. Presenting Results and Drawing Conclusions:

• Clearly present your findings, using tables, charts, or graphs if necessary.

• Connect your results back to your research objectives and draw meaningful conclusions that address the practical implications of your study.

7. Crafting a Well-structured Paper:

• Follow the specific format and guidelines provided by your university or institution.

• Typically, an applied research paper includes sections such as an abstract, introduction, literature review, methodology, results, discussion, and conclusion.

8. Providing Recommendations for Practice:

• Offer practical recommendations based on your research findings. Discuss how these recommendations can be implemented in real-world scenarios.

• Emphasise the actionable nature of your suggestions.

9. Acknowledging Limitations:

• Address any limitations or constraints in your research methodology or data collection.

• Acknowledge potential challenges and discuss their impact on the reliability and validity of your findings.

10. Citing Relevant Literature:

• Ensure proper citation of all sources used in your research. Follow the citation style recommended by your institution.

11. Reviewing and Revising:

• Proofread your paper for clarity, coherence, and grammatical accuracy.

• Seek feedback from peers or mentors and be open to making revisions based on constructive input.

By following these steps, researchers can produce applied research papers that not only contribute to academic knowledge but also offer practical solutions to real-world challenges in their respective fields.

In conclusion, the significance of applied research cannot be understated. With their practical orientation and real-world solutions, they serve as invaluable assets across industries, academia, and societal sectors. They are instrumental in addressing pressing challenges, guiding informed decision-making, fostering innovation, and contributing to positive changes in various fields. Applied research papers bridge the gap between theory and practice, providing actionable insights that enhance efficiency, optimise processes, and lead to tangible improvements. As agents of continuous learning and development, these papers play a pivotal role in shaping the future landscape of industries, organisations, and communities. In a world that demands pragmatic solutions, the importance of applied research papers lies in their ability to make a lasting and meaningful impact on the way we approach and solve real-world problems.

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The difference between basic and applied research – Key differences

 In a rapidly evolving landscape of scientific and technological innovation, understanding the inner workings of research is increasingly vital.

Whether you’re a seasoned academic, an industry professional, or simply a curious individual, comprehending the difference between applied and basic research is used to provide critical insights into how knowledge is both generated and utilized. 

These two kinds of research, while distinct in their aims and methodologies, often serve as two sides of the same coin, each with its unique contributions and challenges.

By examining research outcomes, funding sources, criticisms, and examples from both categories, this comprehensive blog demystifies the often blurry line that separates basic research vs applied research methods. 

If you’ve ever pondered which type of research to use for a project or questioned how basic principles derived from foundational studies turn into real-world applications, this exploration offers a lens into the multifaceted world of research.

Key Differences Between Basic and Applied Research

In the realm of scientific inquiry, understanding the key differences between basic and applied research is crucial. These two types of research serve distinct purposes and often utilize different research methods, but they are interconnected in the quest for new knowledge.

Basic Research

Basic research focuses on the acquisition of fundamental understanding without immediate application in mind. 

For example, when Einstein was formulating his theories in physics, he was conducting basic research.

He sought to explain the laws governing the universe but didn’t necessarily aim to solve a practical problem.

Basic research often gets criticized for not having apparent applications, but it lays the groundwork for future advancements. Years after Einstein, his theories paved the way for the development of laser technology, used in everything from DVDs to medical procedures.

Applied Research

Applied research focuses on solving specific, practical problems. It’s the type of research used when health psychologists want to tackle rising rates of cardiovascular diseases, for instance. Conducting applied research, they may investigate effective messaging strategies to encourage healthier diets, aiming to produce tangible benefits in public health. 

Applied research seeks to utilize scientific understanding for a particular real-world issue.

The line between basic and applied research is not always clear-cut. While applied research may yield new knowledge that contributes to a broader understanding of human behavior, basic research may inadvertently lead to practical applications.

For instance, research in quantum mechanics, which was initially considered highly theoretical, has found applications in modern computing.

It’s also worth noting that the research methods employed may differ based on the type of research being conducted.

Applied research often employs methods like case studies, surveys, or controlled experiments aimed at resolving a specific issue, whereas basic research might involve more theoretical or observational methods aimed at general understanding.

While basic research often explores theoretical concepts without an immediate application, applied research focuses on real-world issues. Both are integral in advancing our collective knowledge and sometimes unexpectedly complement each other in offering solutions to challenges we face.

 What’s better? Basic vs applied research?

The debate between the impact of basic and applied research is an enduring one, and both sides have compelling arguments. The key differences between the two types of research are their aims and methods.

• Basic research focuses on generating new knowledge and understanding fundamental principles, often without an immediate application in mind.
• Applied research, on the other hand, seeks to solve specific problems and is often guided by practical outcomes.

One could argue, as some experts do, that basic research often has a more profound long-term impact. For instance, the discovery of the structure of DNA was a feat of basic research.

Today, it serves as the cornerstone for a multitude of applied research projects in genetics, forensics, and medicine. Another example of basic research is the development of quantum mechanics, which initially appeared to be an abstract field but has led to the invention of technologies like semiconductors and MRI machines.

Conversely, applied research focuses on immediate needs and therefore, its impact can be more immediately visible.

Examples of applied research include the development of COVID-19 vaccines or the creation of energy-efficient technologies. This type of research often uses methods and knowledge generated by basic research to achieve its goals.

The contention that applied research can be counterproductive due to its narrow focus and the push to monetize findings is a nuanced issue.

While entrepreneurship courses in academic settings may appear to detract from the purity of research, they can also offer researchers tools to transform basic research into applied solutions, bridging the gap between theory and practice.

The two aren’t mutually exclusive; basic research and applied research often go hand in hand.

Researchers conducting applied research may stumble upon findings that contribute to new knowledge, just as those conducting basic research may see their work result in unexpected applications.

Examples of basic research vs applied research

Basic research:.

• Genetic Sequencing : Research to understand the sequences of DNA and what each gene does.
• Particle Physics : Experiments in places like CERN to understand the basic building blocks of the universe.
• Social Psychology Theories : Studying human behavior in a controlled environment to understand basic social interactions.
• Climate Models : Researching the fundamental mechanisms that control climate change without necessarily looking for immediate solutions.
• Pure Mathematics : Investigating abstract mathematical concepts that may not have an immediate application.
• Astronomy : Observing and mapping distant celestial bodies to understand the universe’s structure.
• Brain Mapping : Basic research on how neurons communicate within the brain, without a targeted application.
• Evolutionary Biology : Studying how organisms evolve over time to adapt to their environment.

Applied Research:

• Pharmaceuticals : Developing new drugs based on an understanding of disease mechanisms.
• Renewable Energy : Researching better solar panels or wind turbines to harness energy more efficiently.
• Market Research : Understanding consumer behavior to improve product design or advertising strategies.
• Educational Methods : Evaluating teaching strategies to improve educational outcomes.
• Medical Procedures : Research to develop new surgical techniques or medical devices.
• Cybersecurity : Designing new types of encryption or security measures based on vulnerabilities.
• Agricultural Techniques : Researching better ways to increase crop yield or protect against pests.
• Transportation : Developing new materials for lighter, more fuel-efficient vehicles.

Careers in basic research and applied research

Here are some examples of careers that use mainly basic or applied research – but some scientists do a mixture of both.

Careers in Basic Research:

• Theoretical Physicist : Focuses on understanding the fundamental laws governing physical phenomena.
• Astrophysicist : Studies the properties and behaviors of celestial bodies and the universe.
• Mathematician : Conducts research in pure mathematics, exploring abstract concepts.
• Geneticist : Investigates genes, genetic variation, and heredity in organisms.
• Neuroscientist : Researches the complexities of the nervous system, including the brain.
• Biochemist : Studies the chemical processes within and related to living organisms.
• Cognitive Psychologist : Explores the mental processes behind human behavior.
• Archaeologist : Conducts research to understand human history and pre-history through the excavation of sites and the analysis of artifacts.
• Geologist : Studies the Earth’s physical structure and substance, its history, and the processes that act on it.

Careers in Applied Research:

• Pharmaceutical Researcher : Develops new drugs or medical treatments.
• Environmental Consultant : Provides advice on environmental regulations and conducts research to solve environmental problems.
• Data Scientist : Uses statistical models to analyze data for actionable insights, often for businesses.
• Mechanical Engineer : Designs and tests new devices, often focused on solving specific mechanical problems.
• Market Research Analyst : Conducts research to understand market trends and consumer behavior.
• Clinical Psychologist : Applies psychological research to treat mental health disorders.
• Agricultural Scientist : Researches ways to improve the sustainability and productivity of agricultural systems.
• Software Developer : Creates new software based on research into user needs, technological advancements, or problem-solving.
• Nutritional Epidemiologist : Studies the relationship between diet and health outcomes, often aiming for public health applications.

Wrapping up – applied research and basic research

As we’ve journeyed through this comprehensive exploration of applied research and basic research, it’s clear that each holds its unique place in the expansive world of research.

The two are like siblings—different in personality but stemming from the same family of intellectual inquiry.

Basic research is theoretical and often provides the foundation for applied research. On the flip side, applied research is practical in nature and focuses on solving immediate real-world problems.

Despite their differences, one can’t exist optimally without the other.

Basic research helps pave the way for advancements in applied research, while findings from applied research can loop back to enrich our foundational knowledge.

While basic research tends to engage with more conceptual questions, applied research is driven by practical problems that require immediate solutions. These different types of research methods can serve different purposes but are not mutually exclusive.

The world of research is enriched by the interplay between basic and applied research methods. Whether theoretical or practical, long-term or immediate, both contribute significantly to our understanding and make up the vibrant tapestry of research that seeks to answer questions, solve problems, and improve our lives.

And there we have it—your guided tour through the landscape of applied and basic research is complete!

Whether you’re an aspiring researcher, an industry professional, or a curious individual, understanding these key differences between basic and applied research will surely add a valuable layer to your perspective.

Dr Andrew Stapleton has a Masters and PhD in Chemistry from the UK and Australia. He has many years of research experience and has worked as a Postdoctoral Fellow and Associate at a number of Universities. Although having secured funding for his own research, he left academia to help others with his YouTube channel all about the inner workings of academia and how to make it work for you.

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Applied Research Examples: Empowering Real-World Solutions

Understand the meaning of ‘ibid’ and its usage in academic and legal writing. Explore citation practices and raise your referencing skills.

Applied research plays a crucial role in various fields, providing practical solutions to real-world problems and driving advancements in technology, healthcare, business, and more. It bridges the gap between theory and practice by translating scientific knowledge into tangible outcomes that positively impact individuals, organizations, communities, or industries. Applied research enables us to develop innovative solutions, refine existing practices, and make informed decisions based on evidence. By focusing on practical applications, applied research contributes to advancements in various fields, ultimately leading to societal progress and improvement. It serves as a driving force for innovation, economic growth, and the overall betterment of individuals and communities. 

What is Applied Research and its purposes?

Applied research is a systematic and practical approach to investigating real-world problems and finding practical solutions. It makes application of scientific methods and techniques to gather and analyze data, conduct experiments, and make evidence-based recommendations. The primary purpose of applied research is to address specific issues or challenges in various fields. It aims to make better-existing practices, processes, or products, validate the effectiveness of interventions or programs, inform policy decisions, and contribute to the development and implementation of evidence-based strategies. 

When using Applied Research

Some common applications of applied research include:

Business and Marketing

Through the utilization of applied research, organizations can gain valuable insights into consumer behavior, evaluate marketing strategies, assess market trends, and identify opportunities for product development and innovation.

Healthcare and Medicine

Applied research is conducted to evaluate the effectiveness of medical treatments, interventions, and healthcare policies. It helps in the advancement of patient outcomes, optimizes healthcare delivery systems, and informs evidence-based medical practices.

In education, applied research informs curriculum development, evaluates program effectiveness, guides evidence-based instruction, informs policy decisions, supports professional development, and optimizes student assessment and evaluation.

Public Policy and Governance

Policymakers can leverage data-driven insights to inform decision-making, evaluate program effectiveness, and enhance governance practices. This approach fosters evidence-based policymaking, promotes transparency, and facilitates effective and equitable governance.

Environmental Studies

Applied research is used to address environmental challenges, such as climate change, pollution, and natural resource management. It helps develop sustainable practices, assess the environmental impact of policies and projects, and guide conservation efforts.

Technology and Engineering

Optimizing efficiency and advancing technology, applied research in technological and engineering fields develops and upgrades products, systems, and processes, addressing practical problems with innovative solutions.

Agriculture and Food Science

Applied research is conducted to raise agricultural practices and crop yields, ensure food safety, and develop sustainable farming methods. It addresses challenges related to food production, distribution, and environmental impact.

Types of Applied Research

Applied research includes various types tailored to address specific practical issues and inform decision-making. Some common types of applied research are:

Evaluation Research

This type of research focuses on assessing the effectiveness, efficiency, and impact of programs, interventions, policies, or initiatives. It measures outcomes, identifies strengths and weaknesses, and provides recommendations for improvement.

Action Research

Action research involves collaborative inquiry and problem-solving in real-world settings. It emphasizes the active participation of stakeholders to identify and address practical challenges, often leading to immediate changes or interventions.

Research and Development

R&D is a type of applied research with the objective to create innovative products and services to meet market needs. It requires gathering market information, improving existing products, and developing new ones to fulfill customer demands and enhance organizational effectiveness.

Policy Research

Generating evidence-based recommendations for policymakers, policy research plays a crucial role in informing policy development, implementation, and evaluation. By analyzing existing policies and identifying areas for improvement, it aims to shape effective and informed decision-making processes.

Data Collection Methods

Data collection methods refer to the techniques and approaches used to gather information or data for research purposes. These methods vary depending on the nature of the research question, the type of data needed, and the resources available. Here are some common data collection methods:

This collects data through structured questionnaires or interviews. They can be administered in person, over the phone, through mail, or online. Surveys are useful for gathering information from a large number of participants and obtaining self-reported data on attitudes, opinions, behaviors, or demographics.

Interviews conduct one-on-one or group conversations with participants to gather detailed information. Interviews can be structured (with predetermined questions), semi-structured (with a set of guiding questions), or unstructured (allowing for open-ended discussion). Interviews are useful for exploring complex topics, capturing in-depth insights, and understanding participants’ perspectives.

Observations

The method of observation watches and records behaviors, actions, or events in their natural settings. Researchers can be participant observers (actively participating in the observed context) or non-participant observers (observing from a distance). Observations are valuable for studying social interactions, behaviors, and patterns in real-life contexts.

Experiments

Experiments manipulate variables under controlled conditions to determine cause-and-effect relationships. Participants are assigned to different experimental conditions, and data is collected to assess the impact of the manipulated variables. Experiments allow researchers to study causal relationships and test hypotheses.

Data Analysis Methods

Data analysis methods are the techniques and procedures used to analyze and interpret data collected during a research study. These methods help researchers make sense of the data, identify patterns, draw conclusions, and answer research questions. Data analysis plays a crucial role in research as it transforms raw data into meaningful insights and supports evidence-based decision-making. Some common data analysis methods are:

Descriptive Statistics

Descriptive statistics summarize and describe the main characteristics of the data. They include measures such as mean, median, mode, standard deviation, and frequency distributions. Descriptive statistics provide a snapshot of the data’s central tendency, dispersion, and distribution.

Inferential Statistics

Inferential statistics make inferences or draw conclusions about a population based on a sample. These methods help researchers test hypotheses, determine statistical significance, and make generalizations. Examples of inferential statistics include t-tests, analysis of variance (ANOVA), regression analysis, and chi-square tests.

Data Mining

Data mining uses computational algorithms to discover patterns, trends, and relationships within large datasets. It helps identify hidden insights and generate predictive models. Data mining techniques include association rule mining, classification, clustering, and anomaly detection.

Applied Research Methodology

Applied research methodology refers to the systematic approach used to conduct applied research studies. It is a series of steps and procedures designed to gather relevant data, analyze it, and draw meaningful conclusions to address real-world problems or provide practical solutions. The methodology for applied research typically includes the following key components:

Problem Identification

Clearly defining and understanding the specific problem or issue to be addressed is the first step in applied research methodology. Conducting a thorough literature review, consulting with experts, and engaging stakeholders are essential steps to gain insights into the problem’s context, scope, and potential impact.

Research Design

Developing a research design involves determining the appropriate research approach, such as quantitative, qualitative, or mixed methods, based on the research objectives and the nature of the problem. It also includes selecting the appropriate data collection methods, sampling techniques, and data analysis procedures.

Data Collection

Data collection methods are chosen based on the research design and the type of data required. Common data collection methods include surveys, interviews, observations, experiments, case studies, and document analysis. Rigorous data collection techniques ensure the collection of accurate and reliable data relevant to the research problem.

Data Analysis

Data analysis is about processing, organizing, and interpreting the collected data to derive meaningful insights. Depending on the nature of the data, quantitative analysis techniques such as statistical analysis, regression analysis, or data mining may be used. Qualitative analysis techniques, such as thematic analysis or content analysis, can be employed for textual or qualitative data.

Results and Conclusion

The analyzed data is used to draw conclusions, identify patterns, and make inferences related to the research problem. The results are presented in a clear and concise manner, often through tables, charts, or visualizations. Conclusions should be supported by evidence from the data analysis and aligned with the research objectives.

Examples of Applied Research

The applied research examples illustrate how this addresses real-world issues and aims to provide practical solutions that can be implemented and make a meaningful impact in various domains. Here are some applied research examples across different fields:

In healthcare, the focus is finding practical solutions to improve patient care and outcomes. For example, a study investigating the effectiveness of a new medical treatment or therapy for a specific condition would be considered applied research.

The primary objective is to increase teaching methods, curriculum development, and student learning outcomes. This involves evaluating the effectiveness of various instructional approaches and designing interventions to foster improved student engagement and achievement.

In the domain of business and marketing, the emphasis is on tackling practical issues encountered by organizations. This can include analyzing consumer behavior to devise impactful marketing strategies or conducting market research to evaluate the viability of introducing a new product. Such endeavors align with the principles of applied research.

Environmental Science

The objective is to devise practical solutions for addressing environmental challenges. This can encompass studying the effects of pollution on ecosystems, formulating sustainable practices, or assessing the efficacy of conservation initiatives. These pursuits align with the principles of applied research.

Engineering and Technology

The emphasis of applied research on engineering and technology is to create inventive solutions for real-world problems. This could entail research endeavors aimed at enhancing energy efficiency, refining manufacturing techniques, or pioneering novel materials.

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How Applied Research Is Used in Psychology

Verywell / JR Bee

Basic vs. Applied Research

How it works, potential challenges.

• Real-World Applications

Applied research refers to scientific study and research that seeks to solve practical problems. This type of research plays an important role in solving everyday problems that can have an impact on life, work, health, and overall well-being. For example, it can be used to find solutions to everyday problems, cure illness, and develop innovative technologies.

There are many different types of psychologists who perform applied research. Human factors or industrial/organizational psychologists often do this type of research.

A few examples of applied research in psychology include:

• Analyzing what type of prompts will inspire people to volunteer their time to charities
• Investigating if background music in a work environment can contribute to greater productivity
• Investigating which treatment approach is the most effective for reducing anxiety
• Researching which strategies work best to motivate workers
• Studying different keyboard designs to determine which is the most efficient and ergonomic

As you may notice, all of these examples explore topics that will address real-world issues. This immediate and practical application of the findings is what distinguishes applied research from basic research , which instead focuses on theoretical concerns.  

Basic research tends to focus on "big picture" topics, such as increasing the scientific knowledge base around a particular topic. Applied research tends to work toward solving specific problems that affect people in the here and now.

For example a social psychologist may perform basic research on how different factors may contribute to violence in general. But if a social psychologist were conducting applied research, they may be tackling the question of what specific programs can be implemented to reduce violence in school settings.

However, basic research and applied research are actually closely intertwined. The information learned from basic research often builds the basis on which applied research is formed.

Basic research often informs applied research, and applied research often helps basic researchers refine their theories.

Applied research usually starts by identifying a problem that exists in the real world. Then psychologists begin to conduct research in order to identify a solution.

The type of research used depends on a variety of factors. This includes unique characteristics of the situation and the kind of problem psychologists are looking to solve.

Researchers might opt to use naturalistic observation to see the problem as it occurs in a real-world setting. They may then conduct experiments to determine why the problem occurs and to explore different solutions that may solve it.

As with any type of research, challenges can arise when conducting applied research in psychology. Some potential problems that researchers may face include:

Ethical Challenges

When conducting applied research in a naturalistic setting, researchers have to avoid ethical issues, which can make research more difficult. For example, they may come across concerns about privacy and informed consent.

In some cases, such as in workplace studies conducted by industrial-organizational psychologists, participants may feel pressured or even coerced into participating as a condition of their employment. Such factors sometimes impact the result of research studies.

Problems With Validity

Since applied research often takes place in the field, it can be difficult for researchers to maintain complete control over all of the variables . Extraneous variables can also exert a subtle influence that experimenters may not even consider could have an effect on the results.

In many cases, researchers are forced to strike a balance between a study's ecological validity (which is usually quite high in applied research) and the study's internal validity .  

Since applied research focuses on taking the results of scientific research and applying it to real-world situations, those who work in this line of research tend to be more concerned with the external validity of their work.

External validity refers to the extent that scientific findings can be generalized to other populations.

Researchers don't just want to know if the results of their experiments apply to the participants in their studies, rather they want these results to also apply to larger populations outside of the lab.

External validity is often of particular importance in applied research. Researchers want to know that their findings can be applied to real people in real settings.

How It's Used in the Real-World

Here are some examples of how applied research is used to solve real-world problems:

• A hospital may conduct applied research to figure out how to best prepare patients for certain types of surgical procedures.
• A business may hire an applied psychologist to assess how to design a workplace console to maximize efficiency and productivity while minimizing worker fatigue and error.
• An organization may hire an applied researcher to determine how to select employees that are best suited for certain positions within the company.

Applied research is an important tool in the process of understanding the human mind and behavior. Thanks to much of this research, psychologists are able to investigate problems that affect people's daily lives. This kind of research specifically targets real-world issues, however it also contributes to knowledge about how people think and behave.

National Science Foundation. Definitions of research and development: An annotated compilation of official sources .

CDC. Evaluation briefs .

Helmchen H. Ethical issues in naturalistic versus controlled trials .  Dialogues Clin Neurosci . 2011;13(2):173‐182.

Truijens FL, Cornelis S, Desmet M, De Smet MM, Meganck R. Validity beyond measurement: Why psychometric validity is insufficient for valid psychotherapy research .  Front Psychol . 2019;10:532. doi:10.3389/fpsyg.2019.00532

 McBride D.  The Process Of Research In Psychology . SAGE Publications; 2018.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

• Basic vs Applied Research: 15 Key Differences

Based on purpose or utility, a research approach can either be basic or applied. While basic research aims at expanding knowledge by creating new theories and modifying existing ones, applied research is focused on providing practical solutions to specific problems by analyzing empirical evidence. 

There are several meeting and departure points for these approaches, and it is pertinent for every researcher to understand them effectively. In this article, we will be detailing 15 key differences between basic and applied research methods, while also highlighting some similarities between these  research methodologies. 

What is Basic Research?  

Basic research is a research approach that is entirely theoretical and aimed at improving or expanding the knowledge-base of a particular field of study. It focuses on “knowledge for its own sake” and it is primarily driven by curiosity and the need to explore the unknown. 

It is also known as fundamental or pure research and it is a systematic investigation  set  to achieve a better and more detailed understanding of a research subject or phenomenon, not to solve  a specific problem. 

What is Applied Research?  

Applied research is designed to focus on providing  practical solutions to a specific problem. It is a form of investigation that entails  solution-oriented inquiries  into a phenomenon,a field of study or research subject generally employing  empirical methodologies. 

In many cases, applied research is a follow-up research design for basic research because it further investigates the outcomes of pure or basic research in order to validate these findings and apply them to create innovative solutions to specific problems. 

15 Differences Between Basic and Applied Research

• Definition  

Applied research is a research methodology that creates practical solutions for specific problems while basic research is an approach to research that seeks to expand knowledge in a field of study. This means that applied research is solution-driven while basic research is knowledge-specific. 

Basic research seeks to advance the frontiers of knowledge by creating new theories or modifying existing ones. On the other hand, applied research is primarily concerned with creating solutions to problems by collecting and analyzing empirical data in order to arrive at valid research outcomes. 

• Characteristics  

Applied research is primarily defined by its focus on providing a practical solution to a defined problem while basic research is primarily defined by its focus on expanding knowledge. In other words, basic research is theory-oriented, applied research is practical-oriented. 

Applied research is action-oriented and synthetic in nature while basic research is explanatory and analytical in nature. Basic research is solution-specific and primarily concerned with the expansion of knowledge and not with the application of research findings which is the focus of applied research.  

• Advantages of Basic Research over Applied Research

Basic research results in the acquisition of new knowledge and it also expands existing knowledge while applied research does not lead to the acquisition of new knowledge. Applied research only focuses on applying knowledge to solve existing problems hence, it is solution-specific. 

Findings from basic research have been predominantly responsible for breakthroughs in different fields of study while findings from applied research are primarily useful for solving specific research problems. Hence, basic research is universal in nature while applied research is limited in nature. 

• Advantages of Applied Research over Basic Research

Applied research helps organizations and individuals to solve specific problems, unlike basic research that is simply focused on expanding knowledge without providing solutions to existing problems. This, however, does not negate the fact that findings from basic research are useful to proffer  solutions to problems. 

Unlike basic research which  is somewhat subjective in its approach, applied research is an objective method of inquiry. Typically, applied research is unbiased because it arrives at outcomes by subjecting empirical evidence to standardized scientific procedures and this makes it a more valid research method. 

• Examples in Education

In education, applied research is used to improve teaching and learning methods by providing practical solutions to pedagogic problems. On the other hand, basic research is used in education to develop new pedagogic theories that explain different behaviors by teachers and students within the learning environment. 

Examples of basic research in education include: 

• How does the human memory work?
• How do children acquire new languages? 

Examples of applied research in education include: 

• A study to build students’ interests in religious studies.
• A study to improve classroom interaction between teachers and students. 
• Examples in Health

Applied research helps health and medical practitioners to develop evidence-based solutions to pressing health problems. On the other hand, basic research helps medical practitioners to gain insights into different health issues such as the origin and symptoms of diseases and infections which can be useful in developing a cure for such conditions. 

Examples of basic research in health include: 

• An investigation into the secondary symptoms of the Human Papilloma Virus (HPV). 
• An investigation into the symptoms of diarrhea. 

Examples of applied research in health include: 

• An investigation to determine the healing properties of mushrooms.
• An investigation to determine the side effects of alcohol consumption. 
• Examples in Psychology

Applied research is extremely useful in industrial-psychology to create solutions for problems related to workplace behavior, organizational policies and employee recruitment processes. Basic research in psychology is used to gain insights into different psychological conditions in order to understand these behaviors better. 

Examples of basic research in psychology include:

• How do panic attacks happen? 
• What are the symptoms of anxiety disorders? 

Examples of applied research in psychology include: 

• What are the treatment options for anxiety disorders?
• What are the ways to improve employees’ productivity in the workplace? 
• Other Names  

Basic research is also known as pure or fundamental research because it is knowledge-specific while applied research is also referred to as contractual research because of its primary focus on providing a solution to a specific problem. 

Applied research is useful for finding practical solutions to defined problems while basic research is useful for gathering novel information about a concept, phenomenon or field of study. 

Basic research explores the functions and features of newly discovered phenomena in order to improve the understanding of these concepts hence; it fuels scientific and technological innovations. Applied research, on the other hand, helps to provide solutions to improve a specific condition or create new technology. 

• Research Purpose

Basic research is driven by curiosity and the need to explore new areas of knowledge in different fields. On the other hand, applied research is driven by the need to provide answers to specific questions in order to solve a problem. 

This means that applied research is primarily concerned with examining empirical evidence for answers while in basic research, the researcher examines data samples in order to gather more information about them. Such information improves the quality of knowledge of the  subject matter. 

• Research Context

Basic research is conducted in a controlled research environment such as a laboratory while conceptual research is conducted in a real-life setting that is not sterile or restricted. The sterile research context in basic research allows the researcher to strictly observe the behaviors and characteristics of the research subjects. 

In applied research, however, the researcher allows the dependent and independent variables to freely interact with one another in an unrestricted setting where other variables or third factors may intervene. This allows the researcher to have a broader overview of the research problem and arrive at valid and practical solutions. 

• Scope of the Research

Generally, applied research is more limited in scope when compared to basic research. This is because unlike basic research that can be applied to diverse concepts, applied research largely focuses on a specific subject, and its research outcomes are primarily relevant to this subject. 

Because it deals with diverse concepts across different subject matters, basic research is considered a more universal research method than conceptual research. Fundamental research explores knowledge across multiple dimensions in order to gather new information and improve an existing body of knowledge. 

• Theory Formulation

Basic research aims at formulating theories that explain research findings and in the process,  improve   a body of knowledge while applied research aims at arriving at research findings that can solve practical problems. Basic research focuses on principles and theories while applied research focuses on solutions. 

Typically, basic research aims at formulating theories and generalizations that explain a concept, subject or phenomenon and are universally applicable. On the other hand, applied research or conceptual research studies empirical evidence in order to align its findings with a specific problem.  

• Research Outcomes

After carrying out applied research by testing the empirical evidence, the researcher arrives at valid findings or conclusions that confirm or negate the research hypotheses. These findings typically answer the specific research questions, that is, the reason for the applied research. 

On the other hand, at the endpoint of basic research lies new theories, new dimensions to existing theories or new information that improves on a body of knowledge. The outcomes of basic research do not directly serve as innovative solutions to a practical problem. 

• Research Approach

Basic research is theoretical in nature while applied research is practical in nature. In this sense, basic research generates theories and improves on existing theories with the aim of contributing to an existing knowledge bank. 

Applied research, on the other hand, is practical and more descriptive in nature . It is more concerned with the utility and value of research outcomes in terms of their end usage, that is, how they can be used to solve existing problems and develop innovations. 

Are There Similarities Between Applied and Basic Research ? 

• Data Gathering Methods

basic and applied research adopt similar data collection processes in order to gather relevant data and arrive at the most objective research outcomes. They typically make use of qualitative and quantitative data gathering methods such as interviews, questionnaires, surveys, and focus groups to gather information and arrive at research outcomes. 

• Intersectionality

The research outcomes of basic research often serve as the bedrock for applied research.  

• Inductive and Deductive Reasoning

Basic and applied research methods make use of both inductive and deductive reasoning to support the research hypotheses. In deductive reasoning, the researcher moves from the idea to observation, while in inductive reasoning, the researcher transits from observation to the idea. 

Conclusion  

It is important for  researchers to understand the similarities and differences between applied and basic research methods. As  highlighted earlier, the major difference between applied and basic research is the purpose of the research, that is, what the research is set to achieve.

Apart from the purpose of the research, applied and basic research also differ based on the research outcomes, nature of the research and its contexts, to mention but a few. However, both research methods adopt similar data gathering processes including observation and interviews, in order to arrive at objective outcomes. 

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What is applied research anyway?

Revista de Gestão

ISSN : 2177-8736

Article publication date: 5 December 2019

Issue publication date: 5 December 2019

Marotti de Mello, A. and Wood Jr, T. (2019), "What is applied research anyway?", Revista de Gestão , Vol. 26 No. 4, pp. 338-339. https://doi.org/10.1108/REGE-10-2019-128

Emerald Publishing Limited

Copyright © 2019, Adriana Marotti de Mello and Thomaz Wood Jr

Published in Revista de Gestão . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

The above-mentioned question brings no huge mystery. The respected Frascati Manual has a good answer for it. Applied research is original investigation undertaken in order to acquire new knowledge; it is, however, directed primarily towards a specific, practical aim or objective ( OECD, 2015 ). It is about using the existing stock knowledge with the appropriate methodology towards a specific objective, which is usually related to the resolution of a practical problem.

It all would be simple, were it not for the unrestrained creativity of scientists to appropriate, interpret, (re)signify and transmute concepts. This is how the above-mentioned question tends to get different answers, which are influenced by the perspective and personal interest of respondents.

Many scholars advocate that every research in Administration is applied; after all, this is an essentially practical field. It does not mean, however, that executives and entrepreneurs will look forward to the latest edition of Academy of Management Journal or of RAUSP to solve their problems. There is a time and place for everything. It is expected that the significant amount of published articles in good scientific journals contribute for the advance of the administrative science. In some point, the accurate accumulated knowledge will serve as a basis for books, popular articles, lectures and consulting projects, reaching therefore its final destination.

However, there is an increasing unease regarding the functioning of the massive machine that generates such knowledge. Renowned researchers and academic leaders from several areas and places have been criticizing the system for two decades. They affirm that this powerful machine became wicked, too expensive, inefficient, obsessed with precision and focused only on its self-interests, ignoring the real world. There has been several propositions of diagnosis for a structural reform, which involved scientific journals, business schools, academic associations and certification and regulation entities. In short, it is necessary to redirect the system towards its original noble aim: to help managers facing challenges and building a better world.

Institutional changes are always difficult and time-consuming. It is necessary to overcome the interests of established groups and the inertia of embedded practices. Still, several initiatives towards the construction of bridges between theory and practice have been emerging, such as events that gather academics and practitioners, academic journals focused on managers and professional master and doctorate programs. Important agents, such as the Academy of Management , Academy of Management Journal and the Association to Advance Collegiate Schools of Business ( AACSB ) have been showing clear signs of alignment with new times.

Considering the context of change, it is important to invite all the readers of this special edition to consider an important aspect: the differentiation between applicable and applied research. Both are important. An applicable research can contribute to the transformation of reality in different ways. It can bring an original explanation of a new phenomenon or a new explanation for an already known phenomenon. It can still offer a new model to help organizations to solve problems or to benefit from business opportunities.

However, the current scenario seems to ask for the accomplishment of real applied research; i.e. the research that follows Mode 2 production of knowledge (observed by Michael Gibbons and his peers Gibbons et al. (1994) a quarter of century ago): it emerges from a relevant practical issue; it is developed collectively in a multidisciplinary or transdisciplinary way; it results in an effectively implemented solution; and whose quality is evaluated by groups composed of researchers and managers. In short, a research that is demonstrably relevant and accurate.

The conduction of real applied research is a significant challenge. It implies leaving the academia shelter in order to interact with players that have different mindsets, developing the ability to translate scientific knowledge to these players, and, specially, being open to learn from this practice. This is the path we started to follow.

Aligned with this idea, REGE has been accepting applied research papers since 2018. This special issue intends to contribute to the dissemination and development of applied research.

We have received more than 30 papers for this special issue, from Brazil and Latin America. After a careful process of double blind review, six were accepted, bringing a broad view of production in applied research in management, with articles from different regions, countries and research areas.

Gibbons , M. , Limoges , C. , Nowotny , H. , Schwartzman , S. , Scott , P. and Trow , M. ( 1994 ), The New Production of Knowledge: The Dynamics of Science and Research in Contemporary Societies , Sage , London .

OECD ( 2015 ), “ Frascati manual 2015: guidelines for collecting and reporting data on research and experimental development ”, available at: www.conicyt.cl/wp-content/uploads/2014/07/Manual-Frascati-2015.pdf (accessed June 1, 2019) .

Acknowledgements

  REGE would like to thank all the researchers that placed their trust in the journal and submitted their work for the evaluation. The guest editors would also like to thank all reviewers that contributed to this special issue with their precious time and knowledge.

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Methodology

• How to Do Thematic Analysis | Step-by-Step Guide & Examples

How to Do Thematic Analysis | Step-by-Step Guide & Examples

Published on September 6, 2019 by Jack Caulfield . Revised on June 22, 2023.

Thematic analysis is a method of analyzing qualitative data . It is usually applied to a set of texts, such as an interview or transcripts . The researcher closely examines the data to identify common themes – topics, ideas and patterns of meaning that come up repeatedly.

There are various approaches to conducting thematic analysis, but the most common form follows a six-step process: familiarization, coding, generating themes, reviewing themes, defining and naming themes, and writing up. Following this process can also help you avoid confirmation bias when formulating your analysis.

This process was originally developed for psychology research by Virginia Braun and Victoria Clarke . However, thematic analysis is a flexible method that can be adapted to many different kinds of research.

Table of contents

When to use thematic analysis, different approaches to thematic analysis, step 1: familiarization, step 2: coding, step 3: generating themes, step 4: reviewing themes, step 5: defining and naming themes, step 6: writing up, other interesting articles.

Thematic analysis is a good approach to research where you’re trying to find out something about people’s views, opinions, knowledge, experiences or values from a set of qualitative data – for example, interview transcripts , social media profiles, or survey responses .

Some types of research questions you might use thematic analysis to answer:

• How do patients perceive doctors in a hospital setting?
• What are young women’s experiences on dating sites?
• What are non-experts’ ideas and opinions about climate change?
• How is gender constructed in high school history teaching?

To answer any of these questions, you would collect data from a group of relevant participants and then analyze it. Thematic analysis allows you a lot of flexibility in interpreting the data, and allows you to approach large data sets more easily by sorting them into broad themes.

However, it also involves the risk of missing nuances in the data. Thematic analysis is often quite subjective and relies on the researcher’s judgement, so you have to reflect carefully on your own choices and interpretations.

Pay close attention to the data to ensure that you’re not picking up on things that are not there – or obscuring things that are.

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Once you’ve decided to use thematic analysis, there are different approaches to consider.

There’s the distinction between inductive and deductive approaches:

• An inductive approach involves allowing the data to determine your themes.
• A deductive approach involves coming to the data with some preconceived themes you expect to find reflected there, based on theory or existing knowledge.

Ask yourself: Does my theoretical framework give me a strong idea of what kind of themes I expect to find in the data (deductive), or am I planning to develop my own framework based on what I find (inductive)?

There’s also the distinction between a semantic and a latent approach:

• A semantic approach involves analyzing the explicit content of the data.
• A latent approach involves reading into the subtext and assumptions underlying the data.

Ask yourself: Am I interested in people’s stated opinions (semantic) or in what their statements reveal about their assumptions and social context (latent)?

After you’ve decided thematic analysis is the right method for analyzing your data, and you’ve thought about the approach you’re going to take, you can follow the six steps developed by Braun and Clarke .

The first step is to get to know our data. It’s important to get a thorough overview of all the data we collected before we start analyzing individual items.

This might involve transcribing audio , reading through the text and taking initial notes, and generally looking through the data to get familiar with it.

Next up, we need to code the data. Coding means highlighting sections of our text – usually phrases or sentences – and coming up with shorthand labels or “codes” to describe their content.

Let’s take a short example text. Say we’re researching perceptions of climate change among conservative voters aged 50 and up, and we have collected data through a series of interviews. An extract from one interview looks like this:

In this extract, we’ve highlighted various phrases in different colors corresponding to different codes. Each code describes the idea or feeling expressed in that part of the text.

At this stage, we want to be thorough: we go through the transcript of every interview and highlight everything that jumps out as relevant or potentially interesting. As well as highlighting all the phrases and sentences that match these codes, we can keep adding new codes as we go through the text.

After we’ve been through the text, we collate together all the data into groups identified by code. These codes allow us to gain a a condensed overview of the main points and common meanings that recur throughout the data.

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Next, we look over the codes we’ve created, identify patterns among them, and start coming up with themes.

Themes are generally broader than codes. Most of the time, you’ll combine several codes into a single theme. In our example, we might start combining codes into themes like this:

At this stage, we might decide that some of our codes are too vague or not relevant enough (for example, because they don’t appear very often in the data), so they can be discarded.

Other codes might become themes in their own right. In our example, we decided that the code “uncertainty” made sense as a theme, with some other codes incorporated into it.

Again, what we decide will vary according to what we’re trying to find out. We want to create potential themes that tell us something helpful about the data for our purposes.

Now we have to make sure that our themes are useful and accurate representations of the data. Here, we return to the data set and compare our themes against it. Are we missing anything? Are these themes really present in the data? What can we change to make our themes work better?

If we encounter problems with our themes, we might split them up, combine them, discard them or create new ones: whatever makes them more useful and accurate.

For example, we might decide upon looking through the data that “changing terminology” fits better under the “uncertainty” theme than under “distrust of experts,” since the data labelled with this code involves confusion, not necessarily distrust.

Now that you have a final list of themes, it’s time to name and define each of them.

Defining themes involves formulating exactly what we mean by each theme and figuring out how it helps us understand the data.

Naming themes involves coming up with a succinct and easily understandable name for each theme.

For example, we might look at “distrust of experts” and determine exactly who we mean by “experts” in this theme. We might decide that a better name for the theme is “distrust of authority” or “conspiracy thinking”.

Finally, we’ll write up our analysis of the data. Like all academic texts, writing up a thematic analysis requires an introduction to establish our research question, aims and approach.

We should also include a methodology section, describing how we collected the data (e.g. through semi-structured interviews or open-ended survey questions ) and explaining how we conducted the thematic analysis itself.

The results or findings section usually addresses each theme in turn. We describe how often the themes come up and what they mean, including examples from the data as evidence. Finally, our conclusion explains the main takeaways and shows how the analysis has answered our research question.

In our example, we might argue that conspiracy thinking about climate change is widespread among older conservative voters, point out the uncertainty with which many voters view the issue, and discuss the role of misinformation in respondents’ perceptions.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Discourse analysis
• Cohort study
• Peer review
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias
• Social desirability bias

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Caulfield, J. (2023, June 22). How to Do Thematic Analysis | Step-by-Step Guide & Examples. Scribbr. Retrieved September 19, 2024, from https://www.scribbr.com/methodology/thematic-analysis/

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Data Analysis in Research: Types & Methods

What is data analysis in research?

Definition of research in data analysis: According to LeCompte and Schensul, research data analysis is a process used by researchers to reduce data to a story and interpret it to derive insights. The data analysis process helps reduce a large chunk of data into smaller fragments, which makes sense. 

Three essential things occur during the data analysis process — the first is data organization . Summarization and categorization together contribute to becoming the second known method used for data reduction. It helps find patterns and themes in the data for easy identification and linking. The third and last way is data analysis – researchers do it in both top-down and bottom-up fashion.

On the other hand, Marshall and Rossman describe data analysis as a messy, ambiguous, and time-consuming but creative and fascinating process through which a mass of collected data is brought to order, structure and meaning.

We can say that “the data analysis and data interpretation is a process representing the application of deductive and inductive logic to the research and data analysis.”

Why analyze data in research?

Researchers rely heavily on data as they have a story to tell or research problems to solve. It starts with a question, and data is nothing but an answer to that question. But, what if there is no question to ask? Well! It is possible to explore data even without a problem – we call it ‘Data Mining’, which often reveals some interesting patterns within the data that are worth exploring.

Irrelevant to the type of data researchers explore, their mission and audiences’ vision guide them to find the patterns to shape the story they want to tell. One of the essential things expected from researchers while analyzing data is to stay open and remain unbiased toward unexpected patterns, expressions, and results. Remember, sometimes, data analysis tells the most unforeseen yet exciting stories that were not expected when initiating data analysis. Therefore, rely on the data you have at hand and enjoy the journey of exploratory research. 

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Types of data in research

Every kind of data has a rare quality of describing things after assigning a specific value to it. For analysis, you need to organize these values, processed and presented in a given context, to make it useful. Data can be in different forms; here are the primary data types.

• Qualitative data: When the data presented has words and descriptions, then we call it qualitative data . Although you can observe this data, it is subjective and harder to analyze data in research, especially for comparison. Example: Quality data represents everything describing taste, experience, texture, or an opinion that is considered quality data. This type of data is usually collected through focus groups, personal qualitative interviews , qualitative observation or using open-ended questions in surveys.
• Quantitative data: Any data expressed in numbers of numerical figures are called quantitative data . This type of data can be distinguished into categories, grouped, measured, calculated, or ranked. Example: questions such as age, rank, cost, length, weight, scores, etc. everything comes under this type of data. You can present such data in graphical format, charts, or apply statistical analysis methods to this data. The (Outcomes Measurement Systems) OMS questionnaires in surveys are a significant source of collecting numeric data.
• Categorical data: It is data presented in groups. However, an item included in the categorical data cannot belong to more than one group. Example: A person responding to a survey by telling his living style, marital status, smoking habit, or drinking habit comes under the categorical data. A chi-square test is a standard method used to analyze this data.

Learn More : Examples of Qualitative Data in Education

Data analysis in qualitative research

Data analysis and qualitative data research work a little differently from the numerical data as the quality data is made up of words, descriptions, images, objects, and sometimes symbols. Getting insight from such complicated information is a complicated process. Hence it is typically used for exploratory research and data analysis .

Finding patterns in the qualitative data

Although there are several ways to find patterns in the textual information, a word-based method is the most relied and widely used global technique for research and data analysis. Notably, the data analysis process in qualitative research is manual. Here the researchers usually read the available data and find repetitive or commonly used words. 

For example, while studying data collected from African countries to understand the most pressing issues people face, researchers might find  “food”  and  “hunger” are the most commonly used words and will highlight them for further analysis.

The keyword context is another widely used word-based technique. In this method, the researcher tries to understand the concept by analyzing the context in which the participants use a particular keyword.  

For example , researchers conducting research and data analysis for studying the concept of ‘diabetes’ amongst respondents might analyze the context of when and how the respondent has used or referred to the word ‘diabetes.’

The scrutiny-based technique is also one of the highly recommended  text analysis  methods used to identify a quality data pattern. Compare and contrast is the widely used method under this technique to differentiate how a specific text is similar or different from each other. 

For example: To find out the “importance of resident doctor in a company,” the collected data is divided into people who think it is necessary to hire a resident doctor and those who think it is unnecessary. Compare and contrast is the best method that can be used to analyze the polls having single-answer questions types .

Metaphors can be used to reduce the data pile and find patterns in it so that it becomes easier to connect data with theory.

Variable Partitioning is another technique used to split variables so that researchers can find more coherent descriptions and explanations from the enormous data.

Methods used for data analysis in qualitative research

There are several techniques to analyze the data in qualitative research, but here are some commonly used methods,

• Content Analysis:  It is widely accepted and the most frequently employed technique for data analysis in research methodology. It can be used to analyze the documented information from text, images, and sometimes from the physical items. It depends on the research questions to predict when and where to use this method.
• Narrative Analysis: This method is used to analyze content gathered from various sources such as personal interviews, field observation, and  surveys . The majority of times, stories, or opinions shared by people are focused on finding answers to the research questions.
• Discourse Analysis:  Similar to narrative analysis, discourse analysis is used to analyze the interactions with people. Nevertheless, this particular method considers the social context under which or within which the communication between the researcher and respondent takes place. In addition to that, discourse analysis also focuses on the lifestyle and day-to-day environment while deriving any conclusion.
• Grounded Theory:  When you want to explain why a particular phenomenon happened, then using grounded theory for analyzing quality data is the best resort. Grounded theory is applied to study data about the host of similar cases occurring in different settings. When researchers are using this method, they might alter explanations or produce new ones until they arrive at some conclusion.

Choosing the right software can be tough. Whether you’re a researcher, business leader, or marketer, check out the top 10  qualitative data analysis software  for analyzing qualitative data.

Data analysis in quantitative research

Preparing data for analysis.

The first stage in research and data analysis is to make it for the analysis so that the nominal data can be converted into something meaningful. Data preparation consists of the below phases.

Phase I: Data Validation

Data validation is done to understand if the collected data sample is per the pre-set standards, or it is a biased data sample again divided into four different stages

• Fraud: To ensure an actual human being records each response to the survey or the questionnaire
• Screening: To make sure each participant or respondent is selected or chosen in compliance with the research criteria
• Procedure: To ensure ethical standards were maintained while collecting the data sample
• Completeness: To ensure that the respondent has answered all the questions in an online survey. Else, the interviewer had asked all the questions devised in the questionnaire.

Phase II: Data Editing

More often, an extensive research data sample comes loaded with errors. Respondents sometimes fill in some fields incorrectly or sometimes skip them accidentally. Data editing is a process wherein the researchers have to confirm that the provided data is free of such errors. They need to conduct necessary checks and outlier checks to edit the raw edit and make it ready for analysis.

Phase III: Data Coding

Out of all three, this is the most critical phase of data preparation associated with grouping and assigning values to the survey responses . If a survey is completed with a 1000 sample size, the researcher will create an age bracket to distinguish the respondents based on their age. Thus, it becomes easier to analyze small data buckets rather than deal with the massive data pile.

LEARN ABOUT: Steps in Qualitative Research

Methods used for data analysis in quantitative research

After the data is prepared for analysis, researchers are open to using different research and data analysis methods to derive meaningful insights. For sure, statistical analysis plans are the most favored to analyze numerical data. In statistical analysis, distinguishing between categorical data and numerical data is essential, as categorical data involves distinct categories or labels, while numerical data consists of measurable quantities. The method is again classified into two groups. First, ‘Descriptive Statistics’ used to describe data. Second, ‘Inferential statistics’ that helps in comparing the data .

Descriptive statistics

This method is used to describe the basic features of versatile types of data in research. It presents the data in such a meaningful way that pattern in the data starts making sense. Nevertheless, the descriptive analysis does not go beyond making conclusions. The conclusions are again based on the hypothesis researchers have formulated so far. Here are a few major types of descriptive analysis methods.

Measures of Frequency

• Count, Percent, Frequency
• It is used to denote home often a particular event occurs.
• Researchers use it when they want to showcase how often a response is given.

Measures of Central Tendency

• Mean, Median, Mode
• The method is widely used to demonstrate distribution by various points.
• Researchers use this method when they want to showcase the most commonly or averagely indicated response.

Measures of Dispersion or Variation

• Range, Variance, Standard deviation
• Here the field equals high/low points.
• Variance standard deviation = difference between the observed score and mean
• It is used to identify the spread of scores by stating intervals.
• Researchers use this method to showcase data spread out. It helps them identify the depth until which the data is spread out that it directly affects the mean.

Measures of Position

• Percentile ranks, Quartile ranks
• It relies on standardized scores helping researchers to identify the relationship between different scores.
• It is often used when researchers want to compare scores with the average count.

For quantitative research use of descriptive analysis often give absolute numbers, but the in-depth analysis is never sufficient to demonstrate the rationale behind those numbers. Nevertheless, it is necessary to think of the best method for research and data analysis suiting your survey questionnaire and what story researchers want to tell. For example, the mean is the best way to demonstrate the students’ average scores in schools. It is better to rely on the descriptive statistics when the researchers intend to keep the research or outcome limited to the provided  sample  without generalizing it. For example, when you want to compare average voting done in two different cities, differential statistics are enough.

Descriptive analysis is also called a ‘univariate analysis’ since it is commonly used to analyze a single variable.

Inferential statistics

Inferential statistics are used to make predictions about a larger population after research and data analysis of the representing population’s collected sample. For example, you can ask some odd 100 audiences at a movie theater if they like the movie they are watching. Researchers then use inferential statistics on the collected  sample  to reason that about 80-90% of people like the movie. 

Here are two significant areas of inferential statistics.

• Estimating parameters: It takes statistics from the sample research data and demonstrates something about the population parameter.
• Hypothesis test: I t’s about sampling research data to answer the survey research questions. For example, researchers might be interested to understand if the new shade of lipstick recently launched is good or not, or if the multivitamin capsules help children to perform better at games.

These are sophisticated analysis methods used to showcase the relationship between different variables instead of describing a single variable. It is often used when researchers want something beyond absolute numbers to understand the relationship between variables.

Here are some of the commonly used methods for data analysis in research.

• Correlation: When researchers are not conducting experimental research or quasi-experimental research wherein the researchers are interested to understand the relationship between two or more variables, they opt for correlational research methods.
• Cross-tabulation: Also called contingency tables,  cross-tabulation  is used to analyze the relationship between multiple variables.  Suppose provided data has age and gender categories presented in rows and columns. A two-dimensional cross-tabulation helps for seamless data analysis and research by showing the number of males and females in each age category.
• Regression analysis: For understanding the strong relationship between two variables, researchers do not look beyond the primary and commonly used regression analysis method, which is also a type of predictive analysis used. In this method, you have an essential factor called the dependent variable. You also have multiple independent variables in regression analysis. You undertake efforts to find out the impact of independent variables on the dependent variable. The values of both independent and dependent variables are assumed as being ascertained in an error-free random manner.
• Frequency tables: The statistical procedure is used for testing the degree to which two or more vary or differ in an experiment. A considerable degree of variation means research findings were significant. In many contexts, ANOVA testing and variance analysis are similar.
• Analysis of variance: The statistical procedure is used for testing the degree to which two or more vary or differ in an experiment. A considerable degree of variation means research findings were significant. In many contexts, ANOVA testing and variance analysis are similar.

Considerations in research data analysis

• Researchers must have the necessary research skills to analyze and manipulation the data , Getting trained to demonstrate a high standard of research practice. Ideally, researchers must possess more than a basic understanding of the rationale of selecting one statistical method over the other to obtain better data insights.
• Usually, research and data analytics projects differ by scientific discipline; therefore, getting statistical advice at the beginning of analysis helps design a survey questionnaire, select data collection methods , and choose samples.

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• The primary aim of data research and analysis is to derive ultimate insights that are unbiased. Any mistake in or keeping a biased mind to collect data, selecting an analysis method, or choosing  audience  sample il to draw a biased inference.
• Irrelevant to the sophistication used in research data and analysis is enough to rectify the poorly defined objective outcome measurements. It does not matter if the design is at fault or intentions are not clear, but lack of clarity might mislead readers, so avoid the practice.
• The motive behind data analysis in research is to present accurate and reliable data. As far as possible, avoid statistical errors, and find a way to deal with everyday challenges like outliers, missing data, data altering, data mining , or developing graphical representation.

LEARN MORE: Descriptive Research vs Correlational Research The sheer amount of data generated daily is frightening. Especially when data analysis has taken center stage. in 2018. In last year, the total data supply amounted to 2.8 trillion gigabytes. Hence, it is clear that the enterprises willing to survive in the hypercompetitive world must possess an excellent capability to analyze complex research data, derive actionable insights, and adapt to the new market needs.

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Fuzzy-based dilemma assessment in confrontation analysis with applications to the Walkerton Drinking Water Crisis

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Applied computing

Operations research

Decision analysis

Physical sciences and engineering

Earth and atmospheric sciences

Computing methodologies

Artificial intelligence

Knowledge representation and reasoning

Probabilistic reasoning

Vagueness and fuzzy logic

Information systems

Information systems applications

Decision support systems

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• Confrontation analysis
• Fuzzy set theory
• Dilemma assessment
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