Course description

Data Analysis for Psychology in R 2 (DAPR2) is a 2nd year course in data analysis for psychological research, using the R software. This course will introduce you to statistical modelling beyond what is typically taught in an introductory statistics course, empowering you with tools to analyse richer data and answer a broader set of research questions of interest to you.

Course Materials 2020/21

Semester 1

Week	Lecture	Workbook
0	Course Intro	–
1	Preliminaries Functions & Models	Functions & Models
2	Simple Regression: Introduction Simple Regression: Coefficients	Simple Linear Regression
3	Simple Regression: Model Evaluation Simple Regression: Standardised Coefficients	Model Fit
4	Simple Regression: Binary Predictors Simple Regression: Assumption Checks	Assumptions & Diagnostics
5	Simple Regression: Diagnostics Simple Regression: Writing Up	Writing Up
6	– Break Week –	–
7	Multiple Regression I Multiple Regression II	Multiple Linear Regression
8	Interactions I Interactions II	Interactions
9	More on Assumptions More on Diagnostics	More on Assumptions & Diagnostics
10	Model Building	Model Selection
11	– No lecture –	Writing Up

Semester 2

Week	Lecture	Workbook
0	Semester 2 Intro	–
1	Analysing Experimental Designs One Way ANOVA	ANOVA
2	Coding Planned Contrasts Factorial F Tests	Factorial ANOVA
3	Categorical Interactions I Categorical Interactions II	Factorial ANOVA
4	Multiple Comparisons Revising Assumptions	Multiple Comparisons
5	Recapping Experimental Designs	Multiple Comparisons
6	– Break Week –	–
7	Bootstrap Theory Bootstrapping Linear Models	Bootstrapping Regression
8	Logistic Regression I Logistic Regression II	Logistic Regression
9	Intro to GLM Missing Data	More about Logistic Regression
10	Power	Power & Linear Regression
11	Preregistration & Analytic Freedom	–