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a normal population has a mean 100 and variance 25. how large must the sample size be if we want the standard error of the sample average to be at most 1.5

1 Answer

4 votes

Answer:

A sample size of 12 is needed.

Explanation:

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean
\mu and standard deviation(square root of the variance)
\sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
\mu and standard deviation, which is also called standard error,
s = (\sigma)/(√(n)).

In this question:


\sigma = √(25) = 5

How large must the sample size be if we want the standard error of the sample average to be at most 1.5

We need n for which s = 1.5.


s = (\sigma)/(√(n))


1.5 = (5)/(√(n))


1.5√(n) = 5


√(n) = (5)/(1.5)


(√(n))^(2) = ((5)/(1.5))^(2)


n = 11.11

Rounding up

A sample size of 12 is needed.

answered
User JoeLallouz
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