Residual plots can be used to validate assumptions about the regression model.

Homoskedastic refers to a condition in which the variance of the error term in a regression model is constant. Learn more about its importance and how it is used.

The effects on the distribution of least-squares residuals of a series of model mis-specifications are considered. It is shown that for a variety of specification errors the distributions of the least ...

In the context of the classical linear model, the problem of comparing two arbitrary hypotheses on the regression coefficients is considered. Problems involving nonlinear hypotheses, inequality ...

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 ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

Description: An introduction to the modern techniques of econometrics and their applications. Topics include: the classical linear regression model (specification, estimation, inference, and ...

This module will develop your core econometrics skills. The first half of the module provides a grounding in key econometric techniques covering elements such as the classical linear regression model, ...