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Unformatted text preview: Lecture 11 Material Covered in This Lecture: e Chapter 5, Section 5.1: Sampling Distribution for Counts and Proportions h Chapter 5, Section 5.2: The Sampling Distribution of a Sample Mean 1 1. Sample Proportion where X stands for the count of successes in the sample. Proof: Example 1 (Example 5.8, p.342): A sample survey asks a nationwide random sample of 2500 adults if they agree or disagree that "I like buying new clothes, but shopping is often frustrating and timeconsuming." Suppose that 60% of all adults would agree if asked this question. (a). What is the probability that the sample proportion who agree is at least 58%? (Using Minitab). (b). Find the mean and the standard deviation of the sample proportion. 1 2 3 4 5 2. Normal Approximation for Counts and Proportions The idea of sampling distribution!!!!!!!!!! What would happen if we took many samples of size from the population? 1 Simple Random Sample (SRS): A simple random sample of size n consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance to be the sample actually selected. Probability histogram of the sample proportion based on a binomial count with n=2500 and p=0.6. the distribution is very close to a normal.close to a normal....
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This note was uploaded on 07/25/2008 for the course STT 421 taught by Professor Nane during the Summer '08 term at Michigan State University.
 Summer '08
 NANE

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