A method of estimating the parameters of a linear regression model when the covariance matrix is an unknown diagonal matrix is investigated. It is assumed that the ...

When the errors in an ordinary least squares (OLS) regression model are heteroscedastic, hypothesis tests involving the regression coefficients can have Type I error ...

It only makes sense. I did linear regression in google docs and I did it for python. But what if you neither of those? Can you do it by hand? Why yes. Suppose I take the same data from the pylab ...

“The statistician knows...that in nature there never was a normal distribution, there never was a straight line, yet with normal and linear assumptions, known to be false, he can often derive results ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

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, ...

Last month we explored how to model a simple relationship between two variables, such as the dependence of weight on height 1. In the more realistic scenario of dependence on several variables, we can ...

Emily Norris is the managing editor of Traders Reserve; she has 10+ years of experience in financial publishing and editing and is an expert on business, personal finance, and trading. Thomas J ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. David is comprehensively experienced in many facets of financial ...