In multiple regression models, the values of the error variable $\varepsilon$ are assumed to be:
A)autocorrelated.
B)dependent on each other.
C)independent of each other.
D)always positive.

Question

Quizplus · Accepted Answer

In multiple regression models, the error terms ($\varepsilon$) are assumed to be independent of each other, which means that the error for one observation is not influenced by the error of any other observation. This is a key assumption for the validity of standard statistical inference techniques in regression analysis.

In Multiple Regression Models, the Values of the Error Variable ε\varepsilonε

In Multiple Regression Models, the Values of the Error Variable $\varepsilon$