Statistics and Hypothesis Testing

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Practical Hypothesis Testing Form a t-Statistic t ≡ Y act − µ Y ,0 SE(Y ) ◮ µ Y ,0 comes from the null hypothesis ◮ Y and SE(Y ) come from the data. t is approximately distributed N(0, 1) when the sample n is large. We will use the normal approximation for computing the p-value. p-value = 2Φ(− |t|)
The Prespecified Significance Level A standard in the social sciences is that a p-value below 0.05 is appropriate grounds for rejecting the null hypothesis. This corresponds to a t-statistics more than 1.96 (almost exactly 2) standard deviations away from zero. Reject H 0 if p < 0.05 is equivalent to Reject H 0 if |t| > 1.96
Page 1 and 2: Statistics and Hypothesis Testing M
Page 3 and 4: Summary of Main Points ◮ We will
Page 5 and 6: What would be a good way to guess
Page 7 and 8: Y is the least squares estimator of
Page 9 and 10: Random Sampling The consequences of
Page 11 and 12: Hypothesis Testing 1. Gather a samp
Page 13 and 14: The p-Value p-value ≡ Pr H 0 [
Page 15 and 16: How likely is the observed value In
Page 17 and 18: Sample Variance, Sample Standard De
Page 19 and 20: Sample Standard Deviation The sampl
Page 21: Summary: Why standard error ◮ Can
Page 25 and 26: An example Is the mean wage among r
Page 27 and 28: Average wage example, continued ◮
Page 29 and 30: Type I and Type II errors Null Hypo
Page 31 and 32: From Hypothesis Testing to Confiden
Page 33 and 34: Example: 95 percent CI In a sample
Page 35: Next time we do something from the

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