lecture 13 - Lecture 13 Material Covered in This Lecture...

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Lecture 13 Material Covered in This Lecture: 1 Chapter 6, Section 6.2: Tests of Significance 1 2. Tests of Significance Goal: Assess the evidence based on the data in favor of a claim about the population. (1). The reasoning of significant tests A significance test is a formal procedure for comparing observed data with a hypothesis whose truth we want to assess . The hypothesis is a statement about the parameters in a population or model. The results of a test are expressed in terms of a PROBABILITY that measures how well the data and the hypothesis agree Example (Example 6.14): Do middle aged male executives have different average blood pressure than the general population? The national center for health statistics reports that the mean systolic blood pressure for males 35 to 44 years of age is 128 and the standard deviation in this population is 15. The medical director of a company looks at the medical records of 72 company executives in this age group and finds that the mean systolic blood pressure in this sample is X = 126.07. Is this evidence that executive blood pressures differ from the national average? Example 6.7 (p. 400): One purpose of the National Student Loan Survey described in Example 6.3 is to compare the debt of different subgroups of students. For example, the 525 borrowers who last attended a private four-year college had a mean debt of $21200, while those who last attended a public four-year college had a mean debt of $17100. The difference of $4100 is fairly large, but we know that
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these numbers are estimates of the true means. If we took a different
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