John B. answered 04/28/16
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Ok, we're given the population mean mu (24.1) and the population sd sigma (2.5), and we know the population is normally distributed. Per the Central Limit Theorem we know that samples of size n will have
sample means x-bar = mu, and sample standard deviations s = sigma/sqrt(n).
Therefore, z = (24.6 - 24.1)/(2.5/sqrt(66)) = 1.62. From a standard normal table, z = 1.62 equates to a left-tail area of
.9474. Thus, 94.74% of samples of size n=66 taken from this distribution will have sample means of 24.6 or less.
Note: z-score for a sample is: z = (x-bar - mu)/(sigma/sqrt(n))