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applied research notes

6. Topic 5: Data Analysis and Interpretation in Applied Research

Learning Objectives:

By the end of this topic, students will be able to:
✅ Understand different data analysis techniques for qualitative and quantitative research.
✅ Use statistical tools to analyze numerical data.
✅ Interpret qualitative data using coding and thematic analysis.
✅ Visualize and present research findings effectively.

 

5.1 Introduction to Data Analysis

  • Importance of Data Analysis in Applied Research
  • Differences Between Qualitative and Quantitative Data Analysis
  • Ethical Considerations in Data Handling and Interpretation

Discussion Question:

Why is data analysis critical in applied research? Share an example of how data misinterpretation could lead to poor decision-making.

 

5.2 Quantitative Data Analysis

1.      Descriptive Statistics

    • Mean, Median, Mode, Standard Deviation
    • Data Distribution and Normality

2.      Inferential Statistics

    • Hypothesis Testing (T-tests, Chi-Square, ANOVA)
    • Regression Analysis and Correlation
    • Statistical Significance (p-values, Confidence Intervals)

3.      Using Statistical Software

    • Introduction to SPSS, Excel, R, or Python for Data Analysis

Exercise:

Analyze a sample dataset using Excel or an online statistical tool and interpret the results.

 

5.3 Qualitative Data Analysis

1.      Thematic Analysis

    • Identifying Patterns and Themes in Text Data
    • Coding and Categorization

2.      Content Analysis

    • Analyzing Documents, Interviews, and Open-Ended Survey Responses

3.      Using Qualitative Analysis Software

    • Introduction to NVivo or ATLAS.ti for Coding and Analysis

Activity:

Conduct a short interview or focus group, transcribe the responses, and identify key themes.

 

5.4 Data Visualization & Interpretation

  • Creating Graphs, Charts, and Tables (Excel, Tableau, Power BI)
  • Best Practices for Presenting Data Clearly
  • Avoiding Misleading Visual Representations

Case Study:

Analyze a published research study and evaluate how the data is visualized and interpreted.

 

Assessment & Activities for Topic 5

📌 Discussion Post: Compare quantitative and qualitative data analysis methods.
📌 Assignment: Perform a small data analysis using either statistical or thematic methods.
📌 Quiz: Test knowledge on data analysis techniques and tools.