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* Hypothesis Testing * Solution: step1 * Hypothesis Testing * One-side two-side tests: two-side test one-side test * Hypothesis Testing * Definition: A two-side test is a test in which the value of the parameter being studied under the alternative hypothesis are allowed to be either greater than or less than the values of the parameter under the null hypothesis. * Hypothesis Testing * Definition: A one-side test is a test in which the values of the parameter being studied under the alternative hypothesis are allowed to be either greater than or less than the values of the parameter under the null hypothesis, but not both. * Hypothesis Testing * Solution: t =2.69,0.005P0.01 Conclusion: the mean of pulses for healthy males in the mountainous area is higher than that in the general population -2.69 0 2.69 0.005P0.01 Fig.4.1 Demonstration for the current value of t and the P-value P value P value One side * Hypothesis Testing * Exercise 1: Suppose we want to test the hypothesis that mothers with low socioeconomic status (SES) deliver babies whose birth-weights are lower than “normal”. To test this hypothesis, a list is obtained of birth-weights from 100 consecutive, full-term, live-born deliveries from the maternity ward of a hospital in a low-SES area. * Hypothesis Testing * The mean birth-weight is found to be 115 oz, with a sample standard deviation of 24 oz. Suppose we know from nationwide survey based on millions of deliveries that the mean birth-weight in the United States is 120 oz. Can we actually say the underlying mean birth-weight from this hospital is lower than the national average? * Hypothesis Testing * Questions: How to test the hypothesis? What are the type I error and type II errors for the data? What results will be occurred by the errors? * Hypothesis Testing * Solution: step1 * Hypothesis Testing * Step2: -2.08 0 2.08 0.01P0.05 Fig.4.1 Dem
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