Exploring and predicting using linear regression in R
This one-day workshop aims to increase participants understanding of the principles, methods, and interpretation of regression models using the R software environment, a powerful, popular and free statistical and graphical programming language. The scope of the course runs from basic principles of regression methods to interpreting the output of statistical analyses, and also includes practical sessions getting hands-on experience with regression analysis in R.
Recommended Participants
This workshop is relevant to biologists, researchers and generally any student who wishes to expand their skills into regression methods and considering using regression approaches in their research. The workshop is relevant for all disciplines, although examples and exercises will focus on biological datasets. Prior knowledge of R is required (Introduction to R workshop is strongly recommended) as the basics of R will not be covered. Participants are expected to have a basic familiarity with the concepts of descriptive statistics and elementary statistical hypothesis testing.
Learning Objectives
- The workshop will provide attendees with an introduction to the principles of simple and multiple linear regression with R.
Syllabus
- Understand the principles of linear regression methods
- Report and present the output from such analyses
- Run regression models in R
