# STAT 3445 Lecture 24: 12 Advanced Hypothesis Testing(2)

## Document Summary

1 large sample testing: as statisticians, the most common testing situation we will face are situations in which the central limit theorem applies, the typical structure will be along the following lines: Rr = { x > k: we can think of the rr as = { x : x > k} = { x : the variance of the underlying distribution. X is: we also know that under the clt, if our sample is large enough x 0 c x / n imately distributed n (0, 1). This is assuming that e[x1] = 0 is approx: this means that. P (type i error) = p ( x rr| = 0) X 0 c x / n k 0 c x / n}| = 0) = p ( k 0 c x / n: so, if we select k = 0 + z c x / n then our signi cance will be approximately.