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chapter7 - Chapter 7 Sampling and Sampling...

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Chapter 7: Sampling and Sampling Distributions (Sections 3,4,5,6) Objectives: 1. Understand the goal of inferential statistics. 2. Understand what is and how to calculate a point estimate. 3. Understand how a sampling distribution is constructed. 4. Understand the three characteristics of a sampling distribution of the mean. 5. Understand how sample size effects the sampling distribution. 6. Understand the significance of the Central Limit Theorem. 7. Understand how to calculate probabilities about sample means using the sampling distribution. 8. Understand the three characteristics of a sampling distribution of the proportion. 9. Understand how to calculate probabilities about sample proportions using the sampling distribution.
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I. Point Estimation (section 7.3) A. Major Goal of inferential statistics : To make conclusions about the population based upon a single sample. B. Example: 1. Political Pollsters - The sample proportion is used to estimate the actual proportion of the votes that each candidate will get from the population of voters (i.e: those people who actually get out and vote). 2. EAI Example (Page 265)
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II. Introduction to Sampling Distributions (section 7.4) A. Think About This: We do not have the population parameter, say μ . However, hypothetically, if we are to use the sample statistic ( X ) to estimate the population parameter (μ), we should compare our single sample statistic to the sample statistics ( X ’s) obtained from every possible sample.
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