### COMMON MISTEAKS
MISTAKES IN
USING STATISTICS: Spotting and Avoiding Them

# Common Mistakes in Selecting
Terms in Regression

When trying to find a regression model, it is usually
desirable to include as few terms as possible while
still giving a good model. Various procedures have been developed to
help try to decide which explanatory variables can be dropped without
important loss of information. However, these procedures are often used
inappropriately. Here are some common mistakes that may occur in
variable selection.

Assuming linearity is
preserved when terms are dropped

Problems with
stepwise model selection
procedures