Linear regression models predict the outcome of one variable based on the value of another, correlated variable. Excel 2013 can compare this data to determine the correlation which is defined by a ...

The aim of this paper is to prove the validity of smooth residual bootstrap versions of procedures that are based on the empirical process of residuals estimated from a non-parametric regression model ...

Linear regression of a random variable against several functions of time is considered. Limit processes are obtained for the sequences of partial sums of residuals. The limit processes, which are ...

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. Eric's career includes extensive work in both public and corporate ...

Andriy Blokhin has 5+ years of professional experience in public accounting, personal investing, and as a senior auditor with Ernst & Young. Thomas J Catalano is a CFP and Registered Investment ...