Regression in R

Description

All content will be presented via live demonstrations of R programming and data analysis. Workshop participants will practice on-the-fly by following along with the demonstration scripts and completing in-situ practical exercises.

Participants should install both R and Rstudio (the free desktop version) on their computers before the beginning of the course.

• R can be downloaded here.
• RStudio can be downloaded here.
• We will not cover basic R usage. Participants should already know how to use R to read and write data, do basic data manipulations, run R functions, and work with the results returned by R functions.

Although we may briefly discuss the theory underlying the methods covered, we will primarily focus on applying these methods in R.

• Participants should already have some familiarity with the theory of linear regression.
• We will not cover any generalizations of linear regression such as logistic regression, multilevel modeling, or SEM.

Day to Day Documents

Day program S004 - 2025.pdf

Lecturers

Kyle Lang

Target audience

Professionals seeking a master-level introduction to linear regression.

For an overview of all our Winter school courses offered by the Department of Methodology and Statistics please click here.

Aim of the course

After completing this course, participants can:

• Describe how to apply linear regression in R and choose the correct functions with which to implement a given analysis.
• Write basic R scripts to do the following:
  - Run a multiple linear regression model
  - Manipulate the fitted model object produced when estimated a linear regression model
  - Incorporate categorical predictor variables into linear regression models using an appropriate coding      scheme
  - Test for moderation using linear regression and conduct a simple slopes analysis
  - Check the assumptions of the linear regression model via model diagnostics.

Study load

Approximately 8 hours of classroom time.

You will receive a certificate upon course completion. Please be aware that this course does not include graded activities, and therefore, we cannot provide a transcript of grades.

Tags

• R programming
• Linear regression
• general linear model
• winterschool
• M&S