Minneapolis: University of Minnesota, 2016. — 82 p.
What is Linear Regression Model
What is R
What’s next
Missing Values
Sanity Checking & Data Cleaning
Example Data
Data Frames
Accessing a Data Frame
Visualize the Data
The Linear Model Function
Evaluating Quality of the Model
Residual Analysis
Visualizing the Relationships in the Data
Identifying Potential Predictors
Backward Elimination Process
Example of Backward Elimination Process
Residual Analysis
When Things go wrong
Data Splitting for Training & Testing
Training & Testing
Predicting across Data Sets
Reading Data into R Environment
Reading CSV Fles
Few Things to try next
Biblio