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

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

In theory, a linear regression with interactions model can be trained using a closed-form solution that involves computing a matrix inverse. But in practice, a model is usually trained using iterative ...

The estimation is carried out in two steps, the first step being an ordinary least squares regression. The least squares residuals are used to estimate the covariance matrix and the second step is the ...

10.3.1 Scatterplot matrix Recall that we use SAS’s scatterplot matrix feature to quickly scan for pairs of explanatory variables that might be colinear. To do this in R we must first make sure we ...

Learn how to graph linear regression in Excel. Use these steps to analyze the linear relationship between an independent and a dependent variable.

However, many HCCM estimators do not perform well when the sample size is small or when there exist points of high leverage in the design matrix. Prompted by a connection between MacKinnon and White's ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.