In which of the following situations is the assumption of normality least important?
A)If you want only to estimate the parameters of your model.
B)If you have a small sample.
C)If you want to construct confidence intervals around the parameter estimates of your model.
D)If you want to compute significance tests relating to the parameter estimates of your model.

Question

Quizplus · Accepted Answer

The assumption of normality becomes less important with larger sample sizes. Therefore, if you have a small sample, normality may be more important to consider. In the other options, the assumption of normality is important in order to accurately estimate parameters, construct confidence intervals, and conduct significance tests.

In Which of the Following Situations Is the Assumption of Normality