This blog presents four tips that will help you avoid the more common mistakes of applied regression analysis that I identified in the research literature.
This blog looks at why you should resist the urge to add too many predictors to a regression model, and how the adjusted R-squared and predicted R-squared can help!
This blog looks at how to obtain an unbiased and reasonably precise estimate of the population R-squared. It also presents power and sample size guidelines for regression analysis.
Reviewing the basic statistical concepts: expected value and variance.
Low R-squared values are not always bad and high R-squared values are not always good!
