Question

Which of the following statements is correct?

	a.	Residual analysis is the process of examining the residuals from a regression to see if their mean is greater than zero and significant.
	b.	Positive residuals indicate that the actual values of the dependent variable are above the predicted value.
	c.	Negative residuals indicate that the actual values of the dependent variable have measurement errors in them.
	d.	All of the above.

Answer 1

Answer: b) Positive residuals indicate that the actual values of the dependent variable are above the predicted value.

The residual is the actual (observed) value minus the predicted value. If you have a negative value for a residual it means the actual value was LESS than the predicted value. If you have a positive value for residual, it means the actual value was MORE than the predicted value.

Residual analysis is used when the regression model does not fit the data and hence the appropriateness of the model is interpreted with the analysis of residual plots. The difference among the observed value and the predicted value called the residual. These residuals are plotted on a graph called a residual plot. It is done to check if mean and sum of residuals is equal to 0