- CFA Exams
- CFA Level I Exam
- Topic 1. Quantitative Methods
- Learning Module 8. Hypothesis Testing
- Subject 1. The Process of Hypothesis Testing
CFA Practice Question
A result was said to be statistically significant at the 5% level. This means ______
B. the result would be unexpected if the null hypothesis were true.
C. the null hypothesis is probably true.
A. the null hypothesis is probably wrong.
B. the result would be unexpected if the null hypothesis were true.
C. the null hypothesis is probably true.
Correct Answer: B
User Contributed Comments 12
| User | Comment |
|---|---|
| danlan | Null hypothesis is the reverse of the statement. |
| mordja | No, the null hypothesis is what you are testing. The answer is that if the result is statistically significant at 5% it would be unexpected if the null hypothesis was true. |
| natexchang | Can someone elaborate on this please? |
| lourens | They use greek letters in most of formulas, I know now why |
| czar | Significance is the opposite of confidence Interval. Therefore, CI is 95%, i.e. 95% confidence that the null hypothesis is true |
| judylyh | why not A? |
| 2014 | Suppose, if a person does not know that he has aids. Now, he has do the HIV Test. If the test outcome says he has aids. This is statistically significant. So, null hypothesis is true and results were unexpected. I can't explain better than this |
| johntan1979 | Test is done against the null hypothesis, so if the test is statistically significant, reject the null. Saying "the null is wrong" in answer A is a statistically incorrect statement. |
| sshetty2 | I'm thinking that testing at a 5% significance level and seeing a statistically significant result means that you have failed to reject the null. In this case, then, there is only a 5% percent chance of a type 1 error, which is to say, that the null was rejected even when it was true which, by the question's syntax, would be an 'unexpected' result... |
| sshetty2 | Sorry I was wrong above. Seeing a statistically significant result would mean that the null IS rejected. This would then mean that there is only a 5 % chance that the null was rejected incorrectly. |
| dbedford | All this means is that the results of your research hypothesis H1, tended to prove you correct with the 5% chance you are wrong about H1. |
| dbedford | And if H1 is correct then the results you were getting would be unexpected if H1 was not correct but Ho was correct |