Ch20n21Def

# Ch20n21Def - 1 , a 2 , …, a k and probabilities: p 1 , p...

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STAT 110 Chapter 20 and 21 Definitions Central limit theorem – the sampling distribution for the mean of a random sample will become approximately normally distributed as the sample size increases, as long as the original population has a mean and a variance (this works for proportions too, because they are just means) Expected value – found by multiplying each outcome by its probability and then summing over all possible outcomes Given possible outcomes: a
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Unformatted text preview: 1 , a 2 , …, a k and probabilities: p 1 , p 2 , …, p k expected value = a 1 p 1 + a 2 p 2 + … + a k p k Law of large numbers - If a random phenomenon with numerical outcomes is repeated many times independently, the mean of the sample approaches the expected value. The sampling distribution for the proportion from a simple random sample from a large population has (approximately) has mean p and standard deviation ( ) n p p − 1...
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## This note was uploaded on 02/10/2011 for the course STAT 110 taught by Professor Johnson during the Spring '07 term at South Carolina.

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