- CFA Exams
- CFA Level I Exam
- Topic 1. Quantitative Methods
- Learning Module 10. Simple Linear Regression
- Subject 3. Analysis of Variance
CFA Practice Question
Which of the following statements is (are) true with respect to an F-statistic when analyzing a regression model?
II. The t-statistic will not be effective in testing the validity of a linear multiple regression as a whole.
III. In all cases, the calculated F-statistic is simply the square of the calculated t-statistic.
IV. F-statistic is calculated to determine if the coefficients of a linear multiple regression equation are, in aggregate, significant.
I. The calculated F-statistic will decrease as the mean sum of squares of the error terms increases relative to the mean sum of the squares of the regression.
II. The t-statistic will not be effective in testing the validity of a linear multiple regression as a whole.
III. In all cases, the calculated F-statistic is simply the square of the calculated t-statistic.
IV. F-statistic is calculated to determine if the coefficients of a linear multiple regression equation are, in aggregate, significant.
Correct Answer: I, II and IV
III is incorrect because the calculated F-statistic is the square of the calculated t-statistic only when dealing with a simple linear regression.
I is correct because the calculated F-statistic is equal to MSSR/MSSE. As MSSE increases, Fcalc will decrease.
User Contributed Comments 2
| User | Comment |
|---|---|
| vi2009 | II is true ... F-statistics give more weight to test validity of linear multiple regression by testing for weightage of error due explained error by the regresssion model = > someone please confirm. Thanks |
| ericczhang | The t-statistic only tells you about one coefficient, whereas the F-statistic tells you about the entire linear multiple regression. That's why II is true. Although there are certain special cases where the t-stat is equivalent to a F-stat. |