Figure 1: The results of multiple linear regression depend on the correlation of the predictors, as measured here by the Pearson correlation coefficient r (ref. 2). ( a ) Simulated values of ...

We’ll use the R software language to run some examples of multiple linear regression and probit regression using the bayesm package that will illustrate these concepts. Hopefully you'll come away with ...

This short course is intended to provide basic knowledge to graduate students outside the field of statistics to intimate them with the methods and approaches of the classical regression model. Topics ...

Multiple regression is one of the most powerful tools in the basic statistical toolkit. Although simple to apply, it is prone to over- and misinterpretation without attention to diagnostics.