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Simple Linear Regression in R (Self Paced)

Ended May 5, 2021
2 credits

Full course description

Term: Spring 2021

Date & Time: Self-Paced


Instructors: Frances McCarty, Jennifer Van Mullekom, & Katherine Miller

Presented By: Statistical Applications & Innovations Group (SAIG)



Simple Linear Regression is one of the most commonly used statistical methods – but this means it is often misused and misinterpreted. In the SAIG Short Course Simple Linear Regression in R, we will cover the how to perform and interpret simple linear regression. The following topics will be covered:

• Running SLR in R
• Checking SLR assumptions with plots and tests
• Interpreting SLR models and coefficients
• Alternatives if your data don’t meet the usual assumptions

No previous coding experience is required! Bring your laptop with R and RStudio installed on your machine. You can download them from the following links:

If you already have R and RStudio on your laptop, make sure they are the most up to date versions. This course is jointly sponsored by the Statistical Application and Innovations Group (SAIG) and Professional Development Network (PDN).