Timeline for R- testing on the population variance- power of test
Current License: CC BY-SA 4.0
10 events
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| Jan 3, 2022 at 3:19 | comment | added | whuber♦ | @Onyambu I'm not sure what you mean by "do that," because we're discussing a fairly complex situation involving a bunch of steps. But if I'm interpreting things correctly, I believe the crux of the matter is revealed in an illustration I made for a post at stats.stackexchange.com/a/127541/919. It shows the thinking that underlies the post you referenced. Although my explanation is applied to a Normal distribution, it works in exactly the same way for a chi-squared distribution. | |
| Jan 3, 2022 at 3:15 | comment | added | Onyambu | @whuber sorry to bother, but is there a link you could provide that can enable me learn how to do that? | |
| Jan 3, 2022 at 3:13 | comment | added | whuber♦ | @Onyambu That procedure is not inverting the pdf, although in a preliminary step it does indeed find an $x$ at which the pdf has a specified density (so I think I now understand why you might have characterized the test as you did). It is a test based on a shortest-length two-sided confidence interval. The actual p-value calculations invert the cdf, twice. | |
| Jan 3, 2022 at 2:42 | comment | added | Onyambu | @whuber here is the link stats.stackexchange.com/questions/195469/… | |
| Jan 3, 2022 at 2:18 | comment | added | whuber♦ | @Onyambu Could you indicate what "link provided above" refers to? I don't see any links in this thread. | |
| Jan 2, 2022 at 19:22 | comment | added | Onyambu | @whuber in the link provided above, the value 14.6489 was computed from the inverse pdf. ie both 14.6489 and 15.35667 have the same density value. Is that not the inverting the pdf? We also have 17 degrees of freedom. Isnt that the way to compute p-value for two sided chi-sq test? or is the link wrong? | |
| Jan 2, 2022 at 18:55 | comment | added | whuber♦ |
@Onyambu Yes, qchisq inverts the cdf, which is what is needed here. That's simply incorrect that you want to invert the pdf. As I pointed out, the pdf isn't even invertible. It is not involved in computing two-tailed p-values (unless you actually integrate it to compute the cdf!).
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| Jan 2, 2022 at 18:48 | comment | added | whuber♦ |
@Onyambu Re "not readily available in R:" On the contrary, see the help page for qchisq. This is part of the basic R installation. Second, the pdf is not invertible when the degrees of freedom value exceeds $1,$ nor is it applicable in this context anyway. You probably meant to refer to the inverse cdf.
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| Dec 20, 2021 at 1:51 | comment | added | whuber♦ |
You should tell your readers you are sampling from a dataset of 53,940 values. The code hist(replicate(5e2, var(sample(diamonds$carat, 1e3)))) (which takes less than a second to run) will give you the information you need to answer your questions.
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| Dec 20, 2021 at 0:32 | history | asked | floraa | CC BY-SA 4.0 |