![]() ![]() The population proportion ( p) is a parameter that is as commonly estimated as the mean. Sampling Distribution of the Sample Proportion The Central Limit Theorem tells us that regardless of the shape of our population, the sampling distribution of the sample mean will be normal as the sample size increases. A general rule of thumb tells us that n ≥ 30.So if we do not have a normal distribution, or know nothing about our distribution, the CLT tells us that the distribution of the sample means ( x̄) will become normal distributed as n (sample size) increases.The Central Limit Theorem states that the sampling distribution of the sample means will approach a normal distribution as the sample size increases. ![]() Is it normal? What if our population is not normally distributed or we don’t know anything about the distribution of our population? It will have a standard deviation (standard error) equal toīecause our inferences about the population mean rely on the sample mean, we focus on the distribution of the sample mean. ![]()
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