The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate correlation coefficient. If you look at the multiple regression we did, ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to language for statistics, but the "Tidyverse" has given the language a serious ...

In this section, you perform a linear regression showing the relationship between the oxygen consumption rate of subjects while they run and the time it took for the subjects in the FITNESS table to ...

The usual approach to handling missing data in a regression is to assume that the points are missing at random (MAR) and use either a fill-in method to replace the missing points or a method using ...

This example introduces the basic PROC REG graphics syntax used to produce a standard plot of data from the aerobic fitness data set (Example 55.1). A simple linear regression of Oxygen on RunTime is ...

Regression diagnostics and lack-of-fit tests mainly focus on linear-linear regression models. When the design points are distributed on the circumference of a circle, difficulties arise as there is no ...