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Basic Question 1 of 7
True or False? If False, correct the statement.
Suppose you are performing a simple linear regression of Y on X and you test the hypothesis that the slope (β) is zero against a two-sided alternative. You have n = 25 observations and your computed test (t) statistic is 2.6. Then your P-value is given by .01 < P < .02, which gives borderline significance (i.e., you would reject H(0) at α = .02 but fail to reject H(0) at α = .01).
User Contributed Comments 11
| User | Comment |
|---|---|
| woojacky | GOOD |
| Flora0406 | I can't get this one. |
| bmeisner | You need a t table for this to check the p values. It will show you what the answer tells you that t(23, alpha=.02)=+-2.5 and that t(23, .01)=+-2.8. Does anyone remember if we have to memorize the t-values or is that given on the test? |
| xiajessy | yeah, we have to remember t VALUE |
| xiajessy | I mean certain critical t value like at 10% , 5%, 1% significance level, the rest will be provided via a table |
| Nightsurfer | Guys, we won't have to memorize t-values. If this were the normal distribution, perhaps. But t-value is a function of d.f. and confidence. WAY too hard to memorize! |
| Cesarnew | We do not need to memorize any t-values for this question. Just to understand and to interpret the P-value.All the relevant info is given. |
| cfaajay | Guys when P value is given,use that for determining if null hypothesis will be rejected or not..When p-value is less then the level of significance ,reject the null hypothesis for that level of significance as is the case here P value is less then level of significance (0.2) ,so reject null . |
| quanttrader | reject at 0.02 since t > t(critical) fail to reject at 0.01 since t< t(critical) |
| quanttrader | alpha at 0.01 implies a more conservative approach -- ie CL is 99%, and thus it will be harder to reject the null |
| jpowers | Remember this is a two-tailed test. |
I am using your study notes and I know of at least 5 other friends of mine who used it and passed the exam last Dec. Keep up your great work!
Barnes
Learning Outcome Statements
describe the use of analysis of variance (ANOVA) in regression analysis, interpret ANOVA results, and calculate and interpret the standard error of estimate in a simple linear regression
CFA® 2025 Level I Curriculum, Volume 1, Module 10.