Master Multiple Linear Regression

Regression models are used to describe relationships between variables by fitting a line to the observed data.

Multiple linear regression is used to estimate the relationship between two or more independent variables and one dependent variable.

The assumptions of multiple linear regression are homogeneity of variance (homoscedasticity) and independence of observations.

<p>Homogeneity of variance refers to the size of the error in our prediction not changing significantly across the values of the independent variable.</p> Signup and view all the answers

<p>Independence of observations means that the observations in the dataset were collected using statistically valid sampling methods, and there are no hidden relationships among variables.</p> Signup and view all the answers