The Philadelphia Phillies have relied on this budding star to anchor their rotation all season, but he appears to be regressing.

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

In traditional models like linear regression and ANOVA, assumptions such as linearity, independence of errors, homoscedasticity, and normality of residuals are foundational.

R 2 (R-squared) is a statistical measure of the goodness of fit of a linear regression model (from 0.00 to 1.00), also known as the coefficient of determination.

How Homoskedasticity Works Homoskedasticity is one assumption of linear regression modeling, and data of this type work well with the least squares method.

Residual plots can be used to validate assumptions about the regression model. Figure 1: Residual plots are helpful in assessments of nonlinear trends and heteroscedasticity. A formal test of lack ...