Univariate Statistics and Methodology using R
2022/23

Course description

Univariate Statistics and Methodology in R (USMR) is a semester long crash-course aimed at providing Masters students in psychology with a competence in standard statistical methodologies and data analysis using R. Typically the analyses taught in this course are relevant for when there is just one source of variation - i.e. when we are interested in a single outcome measured across a set of independent observations. The first half of the course covers the fundamentals of statistical inference using a simulation-based approach, and introduces students to working with R & RStudio. The latter half of the course focuses on the general linear model, emphasising the fact that many statistical methods are simply special cases of this approach. This course introduces students to statistical modelling and empowers them with tools to analyse richer data and answer a broader set of research questions.

Course materials 2022/23

Week Lecture Workbook
Welcome Week No Lecture A short survey
1 Welcome
Introductions and throwing dice
1A: A first look at R & RStudio
1B: More R - Basic Data Skills
Exercises: Intro R
2 Measurement and Distributions 2A: Measurement & Distributions
2B: Curves & Sampling
Exercises: More R; Estimates & Intervals
3 Testing Statistical Hypotheses 3A: Foundations of Inference
3B: Practical Inference
Exercises: T-tests
4 More Tests 4A: Chi-Square Tests
4B: Revisiting NHST
Exercises: Chi-Square Tests
5 Correlations 5A: Covariance & Correlation
Exercises: Cov & Cor; Models
6 No Lecture Walkthrough: Advanced Data Wrangling
7 Recap
The Linear Model
7A: Simple Linear Regression
Exercises: Simple Linear Regression
8 The Linear Model (ctd) Multiple Linear Regression
Assumptions, Diagnostics & Troubleshooting
Exercises: Multiple Linear Regression
9 Scaling, Contrasts, Interactions 09A: Interactions
09B: Categorical Predictors
Exercises: Interactions & Categorical Predictors
10 The Generalized Linear Model 10A: GLM!
Exercises: Logistic Regression
11 Some Kind of End to the Course Exercises: Tying up loose ends

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