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 ...

Please note: This item is from our archives and was published in 2021. It is provided for historical reference. The content may be out of date and links may no longer function. When teaching cost ...

In this note we examine the bias and small sample efficiency of certain estimators for the parameters of a linear regression function when some observations are missing. The estimators studies in 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 ...

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 ...

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 ...

Statistical tolerance intervals are developed for the normal regression model. These intervals are constructed to guarantee at least P content for all possible values of the predictor variates. The ...