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Unformatted text preview: 1 Realistic Inference about a Population Mean ‘Student’: ordinary guy who hanged changed the world 100 years ago Inferences for μ unrealistically simple case: onclusion about • conclusion about μ • gather data using SRS • σ known • sampling dist. of normal because: − population normal, or x − large sample, normality due to central limit theorem Un realistic Case sampling dist. of normal because x − σ known − population normal, or n large enough that central limit theorem makes sampling distribution normal Un realistic Case equivalently, follows the standard normal distribution → use standard normal dist. to get z* for onfidence interval and P alue for n / x z σ μ = confidence interval and Pvalue for significance test 2 Realistic Inferences for μ more realistic case: • conclusion about μ • gather data using SRS • σ unknown • population distribution singlepeaked with no excessively long tails population μ unknown σ un known ample SRS sample size n calculated x Realistic Case...
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This note was uploaded on 10/16/2011 for the course STAT 05604 taught by Professor Brucejaycollings during the Spring '10 term at BYU.
 Spring '10
 BRUCEJAYCOLLINGS

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