Question

What is said when the errors are not independently distributed?
a) Linearity
b) Heteroscedasticity
c) Autocorrelation
d) Collinearity​

Answer 1

Explanation:

autocorrelation is said when the errors are not independently distributed?

Answer 2

When the errors are not independently distributed it is referred to as heteroscedasticity

• In a heteroscedastic situation, the variance of the errors varies depending on the range of the predictor variable.
• In linear regression models, this may result in skewed or ineffective parameter estimations.
• A new model, such as weighted least squares or a heteroscedasticity-consistent covariance matrix, can be used to solve the problem, or it can be handled by modifying the response variable.
• This concept causes an uneven scatter of the residuals, commonly referred to as the error term, while doing a regression analysis.
• The relationship between income and meal expenses is a well-known illustration of this concept. The variation in food consumption will rise as one's income rises.

#SPJ3