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Unformatted text preview: becomes our random variable, which we call our "statistic". We can now apply the ttest or ztest interpretation of probability. We are now able to determine the probability of a randomly chosen sample mean having a value at least as extreme as our original sample mean. Note that we are implicitly assuming that the null hypothesis is true. This probability is our pvalue which we apply to the original problem. Remember that, in the ttests for differences in means, there is a condition of equal population variances that must be examined. One way to test for possible differences in variances is to do an F test. However, the F test is very sensitive to violations of the normality condition ; i.e., if populations appear not to be normal, then the F test will tend to reject too often the null of no differences in population variances....
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 Spring '08
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