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Reply #18: Null hypotheses [View All]

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Febble Donating Member (1000+ posts) Send PM | Profile | Ignore Mon May-02-05 03:28 AM
Response to Reply #10
18. Null hypotheses
That statement does not refute the whole rBr argument because it is not true. We do not know whether or not response rates were lower in Bush strongholds because they were not statistically significant from the rates in other precinct categories. This means that there is not enough power, either because the numbers of precincts in the extreme precincts is too low or because the variance is too high, or both. But does E-M report not give us the variance.

How you state the null hypothesis depends on the nature of your hypothesis. If a clean fraud-free election was indexed by values in your variables of interest being equal, the null would be a clean fraud-free election. If a clean fraud-free election was indexed by values that are different in your variables of interest, then your null would be fraud. As you say, you are actually better off with the null being "clean", as it means any effects you find allow you to reject the null. Failure to find an effect does not "prove" the null, only allows it to be retained. .

Statistics is blind. You test not innocence or guilt, but whether things are the same or different. All I have done is to demonstrate that bias (and don't jump on me - bias is fraud neutral) was not significantly different in high Bush precincts. The null is retained. The error was randomly distributed. Interpret that as you like.

If you want to demonstrate fraud, you need to frame a testable hypothesis. One hypothesis I would like to see tested is: was the bias greater in precincts in swing states? Or: was the bias greater in Ohio? The null in both these instances would be "the election was fair". This is the best way round. For your purposes. As you say. It is also what I have been doing so far.
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