Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.

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

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

First, multiple linear regression models are considered and the design matrices are allowed to be different. Second, the predictor variables are either unconstrained or constrained to finite intervals ...

Yanming Li, Bin Nan, Ji Zhu, Multivariate Sparse Group Lasso for the Multivariate Multiple Linear Regression with an Arbitrary Group Structure, Biometrics, Vol. 71, No. 2 (JUNE 2015), pp. 354-363 ...

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 ...

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, ...

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