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What happens as sample size increase
the spread decreases and the center becomes more accurate
central limit theorem
must be calculating sample means, samples must be taken independently of each other or n is less than 10% of the population, the population must be normally distributed or the sample size must be at least 30 if above conditions are met, the sampling distribution is approximatley normal, state mean and sd
Determining shape for difference of means
the clt must apply to both means
estimators
stats used to estimate unknown population parameters, biased if the mean is not equal to the mean of the population parameter. as sample size increases, the mean get closer to the true mean
sample variability
the natural tenedency for mean or proportion to differ across sample sizes even if they are taken from the same population, larger samples have less variability