Regression Modelling in R

This workshop will combine an interactive lecture, a practical in R, and a scientific paper interpretation exercise to teach you when and how to apply regression models in R into your research.

Firstly, we will explain the foundational concepts of regression modelling through a short lecture. We will follow this with a practical segment using R in R Studio to apply models to a real, publicly available data. The practical segment will require elementary use of R, but we will provide all necessary scripts (code). We highly recommend you bring your own laptop to class. Finally, we will interpret regression model results from a scientific paper. 

Syllabus

• outcome and predictor variables
• discrete and continuous data
• linear and logistic regression
• correlation
• R-squared and p-value
• regression with a single and multiple predictor variables
• model fitting and checking in R
• model interactions
• model tuning
• model visualisation
• interpret regression model results from scientific papers 

This course is open to Research Degree Students, Postdocs & Research Fellows. Limited spaces available for wider Imperial community.

Learning Outcomes: 

On completion of this workshop, you will be able to: 

• Define and explain fundamental concepts of regression modelling.  
• Formulate, apply, and compare regression models based on a research question.  
• Estimate regression coefficients using R and interpret them in the context of the question.
• Interpret regression model results from scientific papers. 

Prerequisites:

Recommend 'Basic Statistics', 'Introduction to Sampling & Hypothesis Testing', and 'Further Hypothesis Testing'. Basic knowledge of R would be beneficial but is not required and can be obtained from the Introduction to R course.

How to book

• Early Career Researchers (Research Degree Students, Postdocs, Research Fellows) should book via Inkpath using your Imperial Single-Sign-On.
• All other members of the Imperial community, should book here.

Please ensure you have read and understood ECRI’s cancellation policy before booking.