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Unformatted text preview: Central limit T σ Given a population distribution with a mean and a variance μ σ 2, the sampling distribution of the mean using sample size N (or, to put it another way, the distribution of sample means) will have a mean of μ x ̄ = and a variance equal to μ σ 2 = σ 2 , which implies x N ̄ that σ x ̄ = N √ . Furthermore, the distribution will approach the normal distribution as N, the sample size, increases. Only applies to distributions where the mean and variance exist N is the size of each sample, not the number of samples the mean will not change the sd will decrease at a predictable rate dist will approach normal distr as N the sample size increases if already normally distributed, will not change shape cuz it had nowhere to go For any sample size, and any distribution, the sampling distribution of the mean will have a mean value equal to the population mean. 2 For any sample size, and any distribution, the sampling distribution of the mean will have a standard deviation equal to the population...
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This note was uploaded on 10/08/2010 for the course PSY 2801 taught by Professor Guyer during the Summer '08 term at Minnesota.
- Summer '08