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From |
"Verkuilen, Jay" <JVerkuilen@gc.cuny.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: RE: Bootstrapping Conf Intervals - what do they mean? |

Date |
Tue, 3 Jun 2008 17:31:46 -0400 |

Salah wrote: >>JV wrote: "A 95% frequentist confidence interval says that 95% of such intervals you gather will cover the true, fixed parameter" If I understood you correctly, u are saying if one would repeat the experiment 10000 times, 95% of these experiments would result in a confidence interval that covers the unknown population estimate. I could be missing something, but that does not seem to say much about the current confidence interval: the one calculated from this data. How likely that THIS confidence interval covers the true estimate? First of all, I must say I hope I didn't get it backwards! The logic is twisty. Anyway, one of the problems with the frequentist approach is the fact that it seems odd that you can't make probability statements about the thing you want to make inferences about, namely the parameter. What's random is the sampling. Thus in the confidence interval, the only random quantity is the parameter estimate (and its standard error). The parameter is a fixed, but unknown quantity and thus we cannot make probability statements about it. If this seems backwards to you and you want to say things like "there is a 95% chance that the parameter lies in *this* interval", you're going to have to break the Bayesian eggs. Jay * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: RE: Bootstrapping Conf Intervals - what do they mean?***From:*"Salah Mahmud" <salah.mahmud@gmail.com>

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