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

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

In the context of linear regression with dependent and nonstationary errors, the classical moving-block bootstrap (MBB) fails to capture the nonstationarity of the errors. A new bootstrap procedure ...

This paper develops some efficient algorithms for linear spline and piecewise multiple linear regression. A plotting procedure that shows the existence and location of changes in linear regression ...

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, ...

Our procedure involves the application of a weighted linear regression procedure on all height predictions available of an individual (CA and BA-based).

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.