AMS 315 Lecture Notes - Lecture 1: Central Limit Theorem, Type I And Type Ii Errors, Null Hypothesis

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1 be a random sample of size n from y which has the distribution. 2 n: central limit theorem (clt): when. 1 is a random sample of size n from y. , 2 ny which has expected value and variance. For a random sample of size n, it is always true that. The clt allows probability calculations that increase in accuracy as the sample size increases. Yeh: null hypothesis, alternative hypothesis, level of significance , type i error: reject a null hypothesis that is true, the probability of a type i error is . Null distribution is the distribution of the test statistic under the null. 1 hypothesis: type ii error: accept a null hypothesis that is false, typically is set to a small number (0. 05 or 0. 01), and n is chosen so that. , where is dependent on a setting of the alternative hypothesis, is small.

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