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What do you think? A study of any serious substantive problem involves a sequence of incidents at which one is forced to pause and consider what to do next. In an effort to reduce the frequency of misdirected activities one uses statistical tests. I recommend, especially, the example on home ownership. Here are two snippets:. The title of the present session involves an element that appears mysterious to me.
This element is the apparent distinction between tests of statistical hypotheses, on the one hand, and tests of significance, on the other.
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It seem to me that at our discussion, these particular words were used to designate only something like a final outcome of complicated analysis involving several tests of different hypotheses. For example, in the analysis of the follow-up data for the [home ownership] experiment, Mark Eudey and I started by considering the importance of bias in forming the experimental and control groups of families.
As a result of the tests we applied, we decided to act on the assumption or concluded that the two groups are not random samples from the same population.
Acting on this assumption or having reached this conclusions , we sought for ways to analyze that data other than by comparing the experimental and the control groups. My way of providing this has been in terms of severe tests. However, in Neyman-Pearson applications, more than in their theory, you can find many examples as well.
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Joseph P. Department of Statistics. Carlos Vallarino. Michael Wolf. Institute for Empirical Research in Economics.
Ebook Optimality: The Second Erich L. Lehmann Symposium
Cite Citation. Permissions Icon Permissions. Abstract We present a theoretical basis for testing related endpoints. Issue Section:.
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Optimality: The second Erich L. Lehmann symposium
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