The least squares method requires that the variance of the error variable is a constant no matter what the value of x is.When this requirement is violated, the condition is called:
A) heteroscedasticity.
B) homoscedasticity.
C) influential observation.
D) non-independence of .

Question

The least squares method requires that the variance  of the error variable is a constant no matter what the value of x is.When this requirement is violated, the condition is called:
A) heteroscedasticity. 
B) homoscedasticity. 
C) influential observation. 
D) non-independence of .

Quizplus · Accepted Answer

When the variance of the error variable is not constant, it is called heteroscedasticity. This violates the assumption of the least squares method and can lead to biased estimates and incorrect inferences. Homoscedasticity, on the other hand, means that the variance of the error variable is constant, which is the required assumption for the least squares method to work properly. Influential observation and non-independence of the error variable are different issues that may affect the results of the least squares method, but they are not directly related to the assumption of homoscedasticity.

The Least Squares Method Requires That the Variance of the Error