Archive: Statistics for Psychologists
  • Back to the Current Materials
    • 2023/2024
      • PSYC121
        • Statistics for Psychologists
        • 2. Descriptive statistics in RStudio
        • 3. DVs and IVs in RStudio
        • 4. Customisation of graphs, and z-scores
        • 5. Class test
        • 6. Sampling, probability and binomial tests
        • 7. Filtering data and testing means (one-sample t-test)
        • 8. Related-samples t-tests, plotting means and SE bars
        • 9. Unrelated-samples t-test and Power
      • PSYC122
        • 1. Week 11 - Correlation
        • 2. Week 12 - Correlation Part 2
        • 3. Week 13 - The Linear Model
        • 4. Week 14 - Chi-Square
        • 5. Week 16 – Hypotheses, associations
        • 6. Week 17 – Better understanding the linear model
        • 7. Week 18 – Developing the linear model
        • 8. Week 19 – Linear models – critical perspectives
      • PSYC402
        • 1. Recap of the linear model and practising data-wrangling in R
        • 2. Categorical predictors
        • 3. More on interactions
        • 4. Logistic regression
        • 5. Poisson regression
        • Introduction to multilevel data
        • Introduction to linear mixed-effects models
        • Developing linear mixed-effects models
        • Introduction to Generalized Linear Mixed-effects Models
        • Introduction to Ordinal Models
        • How
        • Introduction: the why
        • R knowledge
        • LICENSE
        • References
        • Summary
        • Data visualization
        • What
    • 2024/2025
      • PSYC121
        • Statistics for Psychologists
        • 2. Descriptive statistics in RStudio
        • 3. DVs and IVs in RStudio
        • 4. Customisation of graphs, and z-scores
        • 5. Class test
        • 6. Sampling, probability and binomial tests
        • 7. Filtering data and testing means (one-sample t-test)
        • 8. Related-samples t-tests, plotting means and SE bars
        • 9. Unrelated-samples t-test and Power
      • PSYC122
        • 1. Week 11 - Correlation
        • 2. Week 12 - Correlation Part 2
        • 3. Week 13 - The Linear Model
        • 4. Week 14 - Chi-Square
        • 5. Week 16 – Hypotheses, associations
        • 6. Week 17 – Better understanding the linear model
        • 7. Week 18 – Developing the linear model
        • 8. Week 19 – Linear models – critical perspectives
      • PSYC214
        • Statistics for Psychologists
        • Statistics for Psychologists
        • Statistics for Psychologists
        • Statistics for Psychologists
        • Statistics for Psychologists
        • Statistics for Psychologists
        • Statistics for Psychologists
        • Statistics for Psychologists
        • Statistics for Psychologists
      • PSYC234
        • 1. Review of correlation, simple regression and demonstration of multiple regression
        • 2. Multiple Regression Including Categorical Predictors
        • 3. Multiple Regression Models that Include Interactions (Moderated Variables)
        • 4. Mediation
        • 5. Factor Analysis and the Binomial Test
        • 6. Wilcoxon rank-sum test and Wilcoxon signed-rank test
        • 7. Kruskal-Wallis test and Friedman’s ANOVA
        • 8. Binary logistic regression models
        • 9. Expanding on binary logistic regression
      • PSYC411
        • Week 1. Introducing Data
        • Week 2. Manipulating data
        • Week 3. Drawing graphs from data
        • Week 4. Testing nominal data
        • Week 5. Testing differences between groups
        • Week 6. The structured research report – Quick start
        • Week 6. How you can do the analysis work
        • Week 6. Why we are asking you to do this
        • Week 7. Hypotheses and associations
        • Week 8. Introduction to the linear model
        • Week 9. Data visualization practices
        • Week 10. Developing the linear model
      • PSYC412
        • Week 11. Recap of the linear model and practising data-wrangling in R
        • Week 12. Categorical predictors
        • Week 13. More on interactions
        • Week 14. Logistic regression
        • Week 15. Poisson regression
        • Week 16. Workbook introduction to multilevel data
        • Week 16. Conceptual introduction to multilevel data
        • Week 17. Workbook introduction to mixed-effects models
        • Week 17. Conceptual introduction to mixed-effects models
        • Week 18. Developing linear mixed-effects models
        • Week 18. Conceptual introduction to developing linear mixed-effects models
        • Week 19. Workbook introduction to Generalized Linear Mixed-effects Models
        • Week 19. Conceptual introduction to Generalized Linear Mixed-effects Models
        • Week 20. Workbook introduction to Ordinal (Mixed-effects) Models
        • Week 20. Conceptual introduction to Ordinal (Mixed-effects) Models
        • Week 00. The structured research report – Requirements
        • Week 00. Writing reproducible reports using Quarto
        • LICENSE
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    This is an archive of previous worksheets. They are not updated and if you are looking to follow along with the lectures in the labs, you should return to the homepage and click the appropriate year and then module.

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