Contents

  1. Accessibility Statement

  2. Acknowledgement of Country

  3. Acknowledgements

  4. About the Author

  5. Why do we Need Another Book About Research and Statistics?

    1. My Experience with Statistics
    2. The Philosophy Behind this Little Book
  6. Chapter 1: Research and Statistical Thinking in Everyday Life

    1. 1.1 What can Statistics do for us?

    2. 1.2 If I Apply Statistical Thinking all the Time then why do I find it Difficult?

      1. Causality and Statistics

    3. 1.3 Big Ideas in Statistics

      1. Big Idea 1: Aggregation
      2. Big Idea 2: Variation
      3. Big Idea 3: Modelling
      4. Big Idea 4: Uncertainty
      5. Big Idea 5: Sampling from a Population

    4. 1.4 Data is/are

  7. Chapter 2: Working with jamovi

    1. 2.1 Why jamovi?

      1. How is it Different from SPSS and Other Statistical Software out There?
      2. How is it Different from R (a Statistical Programming Language)?

    2. 2.2 Getting Started with jamovi

      1. Windows
      2. macOS
      3. Other Operating Systems
      4. Getting Started

    3. 2.3 Analyses

      1. Copy and Paste Feature

    4. 2.4 The Spreadsheet

      1. Variables
      2. Filter

    5. 2.5 Loading Data in jamovi

      1. Loading Data from .csv Files
      2. Loading SPSS Files
      3. Loading Excel Files

    6. 2.6 Installing add-on Modules into jamovi

  8. Chapter 3: Brief Review of Research Methods

    1. 3.1 How do we Measure Variables in Psychology?

    2. 3.2 Introduction to Psychological Measurement

      1. What do we Mean by Psychological Measurement?
      2. Variables that we Study in Psychological Research
      3. How do we Measure These Psychological Constructs?
      4. Levels of Measurement
      5. Discrete Versus Continuous Measurements

    3. 3.3 What Makes a Good Measure?

      1. Reliability
      2. Validity

    4. 3.4 Some Complexities

    5. 3.5 The Role of Variables: Predictors and Outcomes

    6. 3.6 Research Design I: Experimental Designs

      1. Experimental Research: Understanding the Causes of Behaviour

    7. 3.7 Research Design II: Non-Experimental Designs

  9. Chapter 4: The Replication Crisis

    1. 4.1 How we Think Science Should Work

      1. How we Think Science Should Work
      2. How Science (Sometimes) Actually Works

    2. 4.2 Reasons for Non-Replication

      1. Questionable Data Practices
      2. Small Sample Sizes
      3. Results may be True for Some People, in Some Circumstances
      4. Systemic Issues

    3. 4.3 What can we do About it?

  10. Chapter 5: Aggregation

    1. 5.1 Why Summarise Data?

    2. 5.2 Summarising Data Using Tables

    3. 5.3 Summarising Data Using Graphs

      1. Why do we Need to Visualise Data?
      2. Plotting Frequencies

    4. 5.4 The Middle of the Data

      1. The Mean
      2. Mode

    5. 5.5 Variability: How Spread Out are the Values?

      1. Variance and Standard Deviation
      2. Range
      3. Homogeneity of Variance

    6. 5.6 Z Scores

  11. Chapter 6: Modelling Variations

    1. 6.1 A Simple Model

      1. What is a Model?

    2. 6.2 Statistical Modelling Using a Single Number

      1. Modelling Height Using a Single Number
      2. Using the Mean as the Model
      3. Summarising Data Robustly Using the Median

    3. 6.3 Sampling and Sampling Error

      1. How do we Sample?

    4. 6.4 The Central Limit Theorem

    5. 6.5 Null Hypothesis Testing

      1. Null Hypothesis Statistical Testing

    6. 6.6 Quantifying Effects

      1. Confidence Intervals
      2. Effect Sizes
      3. Statistical Power
  12. Chapter 7: The General Linear Model

    1. 7.1 General Linear Model

      1. What is the General Linear Model?

    2. 7.2 Modelling Continuous Relationships

      1. Covariation and Correlation
      2. Linear Regression

    3. 7.3 Comparing Means

      1. Comparing a Mean to a Target Value
      2. Comparing Two Means
      3. Comparing Paired Observations
      4. Comparing More than Two Means

    4. 7.4 Working with Categorical Outcomes

    5. 7.5 Introduction to Multivariate Statistical Modelling

  13. Chapter 8: Putting it all Together

    1. 8.1 Practical steps to Statistical Modelling

      1. Getting Help
  14. Chapter 9: Beyond Research and Statistics

    1. 9.1 Beyond Research and Statistics

      1. What is Objectivity and Value Neutrality?
      2. Conclusion

  15. Versioning History

  16. Review Statement