Perhaps the most fundamental type of R analysis is linear regression. Linear regression can be used for two closely related, but slightly different purposes. You can use linear regression to predict ...

Many R commands can be very long. When typing a long command, you can hit the enter key in the middle of the command and R will respond with a "+" prompt indicating that your command is not yet ...

Lesson 9 Simple Linear Regression The purpose of this tutorial is to continue our exploration of multivariate statistics by conducting a simple (one explanatory variable) linear regression analysis.

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

This post will show how to estimate and interpret linear regression models with survey data using R. We’ll use data taken from a Pew Research Center 2016 post-election survey, and you can download the ...

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

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, ...

We introduce a fast stepwise regression method, called the orthogonal greedy algorithm (OGA), that selects input variables to enter a p-dimensional linear regression model (with p ≫ n, the sample size ...