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Probability and Samples, More normal distribution as "n"…
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- More normal distribution as "n" increases to infinity, n = 30 or more, very close to normal, regardless of population distribution
- σ divided by the square root of sample size "n"
- Distribution of sample means will have a mean μ = to population mean.
collection of sample means for ALL possible random samples of a given size (n) that can be obtained from a population
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Characteristics:
- Sample means pile up around population mean (relatively close to pop mean)
- Pile of sample means forms a normal distribution- most samples close to "u", rare to find different
- Larger sample size= closer the sample means to population mean "u"
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σM
Standard Error of M
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Measures how much difference between Population mean μ and sample mean, M
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50% of sample means will be smaller than μ, and 50% will be higher
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the larger the sample size, the smaller the error between M and μ
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