The Central Limit Theorem establishes that the sampling distribution of the sample means with size n can be roughly equivalent to a normal distribution with mean and standard deviation for a normally distributed random variable X, with mean and standard deviation.
The Central Limit Theorem can also be used with skewed variables if n is at least 30.The mean of the sampling distribution of sample means is p for a proportion p in a sapling of size n, and the standard deviation is s=root of p(1-p)/n.This issue involves that:(A) Determine the sample proportion's sampling distribution's mean.The Central Limit Theorem states that 0.85
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