This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily …

This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to …

Jun 21, 2022 · Simple linear regression forecasts metrics based on a relationship between two variables⁠: dependent and independent. The dependent variable represents the forecasted …

Dec 14, 2021 · Single variable linear regression is used to determine the relationship between two variables: the independent and dependent. The equation for a single variable linear regression …

A proof of the FWL theorem and additional insight using regression geometry can be found in Section 2.4 of Russell Davidson and James MacKinnon (2004), Econometric Theory and …

In this simple model, even if we assume that yt 1 and ut are uncorrelated, OLS estimator is still biased. That is because condition 4 is not satis ed: yt 1 depends on ut 1, ut 2 and so on.

Looking at the 2 formulas, we can get formula 2 from formula 1 by a) switching the order of summation; b) switching the names of the indices i <--> k; and c) reversing the order of A and B.

It says that the conditional distribution of y given η is a normal distribution, with mean as a function of the linear combination of fixed and random effects.

When we discuss the linear model we assume that the regressors are exogenous, meaning that they are independent of or uncorrelated with the error term. Often there are reasons to believe …

Mar 31, 2020 · “It’s easy, as you get into these conversations, to get so immersed in one substantive part of the equation that you lose track of what the actual purpose is,” Schlesinger …