Regression Modelling in R
Tutors: Sonja Tang and Fernando Guntoro (GTAs)
Course Level: Level 2
Course Credit: 1 credit
Prerequisites: Recommend 'Basic Statistics', 'Introduction to Sampling & Hypothesis Testing', and 'Further Hypothesis Testing'. Basic knowledge of R would be beneficial.
Duration: 3 hours
Format: Live online or live face-to-face with hands-on practice.
This workshop will combine an interactive lecture and practical modelling to explain how to apply regression methods to model data in terms of one or multiple variables. We will discuss how to approach modelling problems and draw conclusions from correlated variables. This workshop will focus on the application and methods for using regression and will include a practical session followed by how to interpret and analyse your model. The practical session will require very basic level use of R, but all necessary scripts will be provided.
- steps in regression modelling process
- what do we assume?
- residuals and least squares
- regression with a single predictor variable
- multiple explanatory variables
- binary and categorical variables
- model fitting and checking
- model interactions
- explore a general linear model created using R (code will be supplied) on publicly available data
- tune the model
- visualise the model
- interpret regression model results from scientific papers
On completion of this workshop you will be able to:
- Identify the correlation coefficient as a single measure of linear association.
- Apply general linear models to model a response variable in terms of a single or multiple variables.
- Assess model validity by checking model assumptions.
- Evaluate model fitness by comparing the results produced by the model with your data.
- Present model fitness using data visualisation techniques.
- Interpret regression model results from scientific papers.
Dates & Booking Information
- Friday 09 June 2023, 10:00-13:00, South Kensington (In-Person Teaching)
To book your place, please follow the booking process advertised on the main programme page