Goodness-of-fit statistics for general multiple-linear-regression equations are reviewed for the case of replicated responses. A modification of the coefficient of determination is recommended. This ...

In order to introduce the concepts underlying multiple linear regression, it is necessary to be familiar with and understand the basic theory of simple linear regression on which it is based.

It can be highly beneficial for companies to develop a forecast of the future values of some important metrics, such as demand for its product or variables that describe the economic climate. There ...

Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...

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 ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

In a transformation model h(Y) = X'β + ε for some smooth and usually monotone function h, we are often interested in the direction of β without knowing the exact form of h. We consider a projection of ...

Linear regression is one of the simplest and most useful tools for analyzing data. It helps you find the relationship between variables so you can make predictions and understand patterns. In this ...

When you perform regression analysis in Microsoft Excel, you are engaging in a statistical process that helps you understand the relationship between variables. This technique is particularly useful ...