STAB22H3 Chapter Notes - Chapter 15 - 17: Central Limit Theorem, Simple Random Sample, Confidence Interval
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STAB22H3 Full Course Notes
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Normal underlying distribution of population: sizes increases, the variance decreases. ) bigger. Sampling distribution: is a random distribution used in statistics. The sd of n decreases as n increases. (as sample. N can estimate the mean better if the sample size is. Uses an srs of a sample size, n, from a population with a mean, , and sd, . When the sample size, n, is large, the sampling distribution of a sample mean, , is approximately normal with the mean, , and sd = . The sd decreases as n increases (the variance. Central limit theorem: decreases as the sample size increases. ) When x is considered as the count of success in the sample, is the sample proportion of successes, = When n is large, the sampling distributions are approximately normal: Confidence interval: a plausible range of values for a parameter. P = population proportion (true probability of success, unknown) N = sample size (number of trials)
