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Model Selection in R

Course Date: Course Not Offered This Semester

Who This Course Is For

Regression is one of the most commonly used statistical methods – but things can quickly get complicated when you have multiple predictors. In the SAIG Short Course Model Selection in R, we will cover different methods to evaluate different regression models with different sets of predictors.



Duration:  2 hours

Course Dates: Available On Demand

Venue: Self-paced

Required Software:  R & R Studio (free)

Cost: Free to VT Participating Colleges and Administrative Units

Pre-requisites:  No previous coding experience is required.  Knowledge of basic descriptive statistics is assumed.

Prework includes downloading course materials, R, and R Studio.

By the end of this course you will be able to:


  • Runn Multiple Linear Regression in R
  • Check MLR assumptions with plots and tests 
  • Applying model selection methods like stepwise regression & LASSO
  • Criterion used to assess models (AIC, BIC, etc.)


This is a hands-on, interactive course where you will submit pre-written code followed by exercises where you write your own code based on examples.  You will leave with code that you can apply to your datasets.