Answer: The standard deviation of the sampling distribution of M is equal to the standard deviation of the population divided by the square root of the sample size.
You can assume that the sampling distribution of M is normally distributed for any sample size.
Step-by-step explanation:
- According to the central limit theorem , if we have a population with mean
and standard deviation
, then if we take a sufficiently large random samples from the population with replacement , the distribution of the sample means will be approximately normally distributed. - When population is normally distributed , then the mean of the sampling distribution = Population mean

- Standard deviation of the sampling distribution =
, where
= standard deviation of the population , n= sample size.
So, the correct statements are:
- You can assume that the sampling distribution of M is normally distributed for any sample size.
- The standard deviation of the sampling distribution of M is equal to the standard deviation of the population divided by the square root of the sample size.
we just have to find x
so,
20-x=6
do it like this
-x = 6-20
-x = -14
x = 14 is the write answer
Answer:
$68
Step-by-step explanation:
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The answer is in the attachment