The multiple linear regression model assumes:
A) the mean error is zero, error variance is nonconstant, and the errors are independent and normally distributed.
B) the mean error is not zero, error variance is constant, and the errors are independent and normally distributed.
C) the sample size is large (at least 30), and errors are independent and normally distributed.
D) the mean error is zero, error variance is constant, and the errors are independent and normally distributed.

Question

Quizplus · Accepted Answer

The multiple linear regression model assumes that the mean error is zero (i.e., the errors are unbiased), the error variance is constant (i.e., the errors have the same variance for all values of the independent variables), and the errors are independent and normally distributed (i.e., the errors are randomly distributed around zero with a normal distribution). While a large sample size and normally distributed errors are important, these assumptions alone do not fully capture the requirements of the multiple linear regression model. Choice A is incorrect because it assumes non-constant error variance. Choice B is incorrect because it assumes non-zero mean error. Choice C is incorrect because it assumes that a large sample size is the only requirement for the model.

The Multiple Linear Regression Model Assumes