ST512. Lab 2 KEY. 1. Answers will vary. 2. 1.734 3. Answers will vary. Observed type I error rate when variances are equal should be approximately 5%. Observed type I error rate when variances are not equal should be around 7-10%. 4. In this case, unequal variances inflates the Type I error rate of the standard 5% significance level test. That is to say, using the standard t-test would lead one to reject a true null hypothesis more than 5% of the time. Thus, p-values and reject / do not reject decisions are not trustworthy. 5. Even when all the assumptions are appropriate, there is an element of randomness in whether a true null hypothesis is rejected in any single data set, or in any collection of data sets. Thus, we wouldn't expect the observed type I error rate to be exactly equal to the significance level, even if the test is performing as it should. This is a bit like flipping a biased coin.
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