Statistics for Group Comparisons

Welcome to PSYC214: Statistics for group comparisons

Teaching team: Sam Russell and Mark Hurlstone (module coordinator)

In this module, you will learn about a statistical technique for performing group comparisons known as Analysis of Variance (ANOVA). It is one of the most common statistical techniques, so it is important to have a thorough understanding of it, which is why we are devoting an entire module to the technique. We will cover a range of statistical tests associated with ANOVA, starting with designs involving a single independent variable (single factor designs), before moving onto designs involving multiple independent variables (factorial designs). We will also cover various follow-up procedures (procedures for identifying which specific conditions differ from one another), including planned comparisons and post-hoc tests, and how to interpret interactions (when the effect of one independent variable depends on the effect of another independent variable, and vice versa). The R statistical package is used throughout and students are expected to develop the skills for conducting appropriate analyses and interpreting the resulting output.

Structure and Content:

Weeks 1-5: Single-Factor Designs - Taught by Dr Sam Russell

  • Week 1: Measurement, Variance and Inferential Statistics

  • Week 2: One-Factor Between-Participants ANOVA

  • Week 3: Assumptions of ANOVA and Follow-Up Procedures

  • Week 4: One-Factor Within-Participants ANOVA

  • Week 5: Interim Summary

Weeks 6-10: Factorial Designs - Taught by Dr Mark Hurlstone

  • Week 6: Introduction To Factorial Designs

  • Week 7: Two-Factor Between-Participants ANOVA

  • Week 8: Two-Factor Mixed and Within-Participants ANOVA

  • Week 9: Three-Factor ANOVA

  • Week 10: Class Test

Course Contacts

Email Address
Sam Russell
Mark Hurlstone
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