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Estimation and Hypothesis Testing for Two Population Parameters参考
Chapter 9 Estimation and Hypothesis Testing for Two Population Parameters Chapter Goals After completing this chapter, you should be able to: Test hypotheses or form interval estimates for two independent population means Standard deviations known Standard deviations unknown two means from paired samples the difference between two population proportions Estimation for Two Populations Difference Between Two Means Independent Samples Different data sources Unrelated Independent Sample selected from one population has no effect on the sample selected from the other population Use the difference between 2 sample means Use z test or pooled variance t test σ1 and σ2 known σ1 and σ2 known σ1 and σ2 known σ1 and σ2 unknown, large samples σ1 and σ2 unknown, large samples σ1 and σ2 unknown, large samples σ1 and σ2 unknown, small samples σ1 and σ2 unknown, small samples σ1 and σ2 unknown, small samples σ1 and σ2 unknown, small samples Paired Samples Tests Means of 2 Related Populations Paired or matched samples Repeated measures (before/after) Use difference between paired values: Eliminates Variation Among Subjects Assumptions: Both Populations Are Normally Distributed Or, if Not Normal, use large samples Paired Differences The ith paired difference is di , where Paired Differences The confidence interval for d is Hypothesis Tests for the Difference Between Two Means Testing Hypotheses about μ1 – μ2 Use the same situations discussed already: Standard deviations known or unknown Sample sizes ? 30 or not ? 30 Hypothesis Tests forTwo Population Proportions Hypothesis tests for μ1 – μ2 σ1 and σ2 known σ1 and σ2 unknown, large samples σ1 and σ2 unknown, small samples Hypothesis tests for μ1 – μ2 Pooled sp t Test: Example You’re a financial analyst for a brokerage firm. Is there a difference in dividend yield between stocks listed on the NYSE NASDAQ? You collect the following data: NYSE NASDAQNumber
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