If, for a multiple regression, you have many variables and not enough participants in the analysis, then the statistics will be:
A)pessimistic, they may fit the sample very well, but might not generalise to the population
B)pessimistic, they may not fit the sample very well and they will not generalise to the population
C)optimistic, they may not fit the sample very well but they will generalise to the population
D)optimistic, they may fit the sample very well, but might not generalise to the population

Question

Quizplus · Accepted Answer

When there are many variables and not enough participants in a multiple regression analysis, the model may overfit the sample data, leading to optimistic statistics that appear to fit the sample very well but may not generalize well to the broader population. This is because the model may capture noise or random fluctuations in the sample data as if they were meaningful patterns, which likely do not apply to other data sets.

If, for a Multiple Regression, You Have Many Variables and Not