Linear regression is a type of data analysis that considers the linear relationship between a dependent variable and one or more independent variables. It is typically used to visually show the ...

When teaching cost behavior in a managerial or cost accounting course, we explain that there are various methods a company can use to estimate its fixed and variable costs, including regression ...

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

The statistical literature and folklore contain many methods for handling missing explanatory variable data in multiple linear regression. One such approach is to incorporate into the regression model ...

One common problem in the use of multiple linear or logistic regression when analysing clinical data is the occurrence of explanatory variables (covariates) which are not independent, ie ...

As in Excel, we can manually remove explanatory variables one-by-one until we have a model in which all the explanatory variables are significant. This is the essence of data-driven (versus theory ...

A linear regression is a statistical model that attempts to show the relationship between two variables with a linear equation. A regression analysis involves graphing a line over a set of data ...

This paper provides an alternative approach to penalized regression for model selection in the context of high-dimensional linear regressions where the number of covariates is large, often much larger ...