lec20 - STATISTICS 13 Lecture 20 Review Sampling...

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STATISTICS 13 Lecture 20 Nov 19, 2012
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Review Sampling distribution Random samples Standard error Central Limit Theorem (CLT) Sampling distribution of Sample mean
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n / σ x In Summary: Sampling Distribution of Sample Mean A random sample of size n is selected from a population with mean µ and standard deviation σ. Τ he sampling distribution of the sample mean has mean µ and standard deviation . If the original population is normal , the sampling distribution is normal for any sample size. If the original population is non-normal , the sampling distribution will be approximately normal when n is large
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Computing Probabilities Involving Sampling Distribution of Sample Mean When sample size n is large or the underlying population distribution is normal, the sampling distribution of is (approximately) normal. Then to calculate , we can standardize the interval of interest in terms of z-values: x ) ( ), ( a x P a x P < > n a z / σ µ =
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Example: Body Temperature Suppose the temperatures of healthy humans is approximately normal with a mean of 98.6 degrees and a standard deviation of 0.8 degrees
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lec20 - STATISTICS 13 Lecture 20 Review Sampling...

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