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- From: jerry@ginger.hnrc.tufts.edu (Jerry Dallal)
- Newsgroups: sci.math.stat
- Subject: Inference
- Message-ID: <1992Aug19.124712.305@ginger.hnrc.tufts.edu>
- Date: 19 Aug 92 17:47:12 GMT
- References: <1992Aug14.172833.11844@cbfsb.cb.att.com> <c48nbgtf@csv.warwick.ac.uk> <WVENABLE.92Aug18180002@algona.stats.adelaide.edu.au> <1992Aug18.214711.6657@mailhost.ocs.mq.edu.au>
- Organization: USDA HNRC at Tufts University
- Lines: 18
-
- In article <1992Aug18.214711.6657@mailhost.ocs.mq.edu.au>, wskelly@laurel.ocs.mq.edu.au (William Skelly) writes:
- > I am not sure I follow you. From my applications I only want to test
- > some null-hypothesis (perhaps a narrow application...but very useful!).
- > Generally I want to know if two samples are from the same population.
- > Isn't this just asking whether or not the two sample means are close?
- >
-
- Heck, *NO*!!!
-
- Suppose you have two safety devices. Both are inexpensve to manufacture,
- install, and replace, compared to the consequences of their failure.
- One has failure times that follow a
- normal distribution with a mean of 10 years and a standard deviation of 1 day.
- The other has failure times that follow a
- normal distribution with a mean of 10 years and a standard deviation of
- 3 years. I hope you wouldn't be indifferent in choosing a
- device to use when your test of significance fails to reject the null
- hypothesis of equal population means.
-