tag:blogger.com,1999:blog-4594832939334410220.post3267863999749484923..comments2024-07-15T09:13:26.823-05:00Comments on Deeply Trivial: Statistics Sunday: On Birthdays, and One-Tailed and Two-Tailed TestsUnknownnoreply@blogger.comBlogger4125tag:blogger.com,1999:blog-4594832939334410220.post-76772524352844034512018-01-08T09:36:39.746-06:002018-01-08T09:36:39.746-06:00I think what I've learned in my exposure to an...I think what I've learned in my exposure to and experience with statistics over the years is that there are always a series of trade-offs one must make. In reducing Type I error, we increase our risk of Type II error, and vice versa. The trade-off with a one-tailed test is that, though you get essentially double the alpha (but not really), it's only for one direction of difference. A difference in the other direction, no matter how large, must be discounted, because you traded direction for double alpha. Either way, your alpha is the same; it's just a question of whether you want the increased power to detect an effect in only one direction, or to be open to the possibility that the direction could go either way. The two commenters above makes excellent points that one-tailed tests are probably best used in situations where only one direction is possible or logical. And obviously, the whole one- versus two-tailed dichotomy doesn't apply to many analyses. So for the most part, tests will be two-tailed, either by choice or necessity.Sarahttps://www.blogger.com/profile/13213593768515404983noreply@blogger.comtag:blogger.com,1999:blog-4594832939334410220.post-90028118797506610222018-01-08T09:20:19.965-06:002018-01-08T09:20:19.965-06:00Why is it relevant, other than to convince the kin...Why is it relevant, other than to convince the kind of journal editor who thinks this sort of thing is meaningful or important, to "maximize the chance that you'll find a significant effect"? Why not just double my alpha to .10? How, in practice, is that different?Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-4594832939334410220.post-31189190202927721092018-01-07T12:53:47.263-06:002018-01-07T12:53:47.263-06:00In most applications a one sided hypothesis is onl...In most applications a one sided hypothesis is only tenable if you can logically discount one of the two possibilities. There are situations where a one sided test is permissible e.g. interim analyses for trial progression or to meet certain statutory requirements. Usually though one sided tests and one sided confidence intervals are not justifiable. Wishful thinking is not a justification. Anonymoushttps://www.blogger.com/profile/01145824413185360386noreply@blogger.comtag:blogger.com,1999:blog-4594832939334410220.post-86600786381192459822018-01-07T11:35:37.722-06:002018-01-07T11:35:37.722-06:00IMO, a one-tailed test should be used only when th...IMO, a one-tailed test should be used only when the other tail is an impossibility. You've a you're/your typo here "remember what it is your testing" DrJBNhttps://www.blogger.com/profile/11654447833923774607noreply@blogger.com