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lecture13

lecture13 - Review Statistical Power Hypothesis testing...

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Review: Statistical Power Hypothesis testing with the t-test A new type of t http://www.stat.sc.edu/%7eogden/javahtml/ power/power.html z = M ± ± ² M t = M ± ± s M z = M ± ± ² 2 n t = M ± ± s 2 n Sample variance Population variance testStatistic = Difference between data and hypothesis standard distance expected by chance

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± M = ± n = ± 2 n sample variance = s 2 = SS n ± 1 = SS df M s = s 2 n Estimated standard error t-test population variance not known z-test population variance known 1. State the hypothesis (null and alternative) 2. Set the decision criterion Locate the critical t for the speci ed alpha using the appropriate df and table B.2 3. Collect sample & compute statistic compute mean, sample variance, and t-statistic 4. Compare statistic to criterion and make a decision apply same logic as with a z-test (if obtained t falls in critical region, then reject the null) 36 workers are switched to a compressed schedule (3 consecutive 13-hour shifts). They rate their preference on a scale from 1-10 (0=prefer standard, 5=no preference, 10= prefer compressed).
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