Regression Analysis > Hausman Test You may want to read this article first: What is an endogenous variable? What is the Hausman Test? The Hausman Test (also called the Hausman specification test) detects endogenous regressors (predictor variables) in a regression…

# Simultaneous Equations Model (SEM): Simple Definition

Regression Analysis > Simultaneous Equations Model (SEM) You may want to read this other article first: What is Simultaneity? What is a Simultaneous Equations Model (SEM)? A Simultaneous Equation Model (SEM) is a model in the form of a set…

# Reverse Causality: Definition, Examples

Regression Analysis > Reverse Causality What is Reverse Causality? Reverse causality means that X and Y are associated, but not in the way you would expect. Instead of X causing a change in Y, it is really the other way…

# Instrumental Variable: Definition & Overview

Regression Analysis > Instrumental Variable What is an Instrumental Variable? An instrumental variable (sometimes called an “instrument” variable) is a third variable, Z, used in regression analysis when you have endogenous variables — variables that are influenced by other variables…

# General Linear Model (GLM): Definition / Overview

Probability and Statistics > Regression analysis > General Linear Model (GLM) What is a General Linear Model? The General Linear Model (GLM) is a useful framework for comparing how several variables affect different continuous variables. It is the foundation for…

# Beta Weight: Definition, Uses

Regression Analysis > Beta Weight What is a Beta Weight? A beta weight is a standardized regression coefficient (the slope of a line in a regression equation). They are used when both the criterion and predictor variables are standardized (i.e.…

# Logistic Regression (Logit Model): a Brief Overview

Probability and Statistics > Regression Analysis > Logistic Regression / Logit Model In order to understand logistic regression (also called the logit model), you may find it helpful to review these topics: The Nominal Scale. What is Linear Regression? Simple…

# Assumptions and Conditions for Regression

Probability and Statistics > Regression Analysis > Assumptions and Conditions for Regression Assumptions and Conditions for Regression. Regression can be a very useful tool for finding patterns in data sets. However, your data can’t always be fit to a regression…

# Standard Error of Regression Slope

Probability and Statistics > Regression Analysis > Standard Error of Regression Slope Standard Error of Regression Slope: Overview Standard errors for regression are measures of how spread out your y variables are around the mean, μ.The standard error of the…

# Lowess Smoothing in Statistics: What is it?

Statistics Definitions > Lowess Smoothing Lowess Smoothing: Overview LOWESS (Locally Weighted Scatterplot Smoothing), sometimes called LOESS (locally weighted smoothing), is a popular tool used in regression analysis that creates a smooth line through a timeplot or scatter plot to help…