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Basic Question 7 of 7
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.
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. |
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Learning Outcome Statements
formulate hypotheses on the significance of two or more coefficients in a multiple regression model and interpret the results of the joint hypothesis tests;
CFA® 2025 Level II Curriculum, Volume 1, Module 2.