Define the distribution of sample means. Then describe its shape and the two conditions that could cause the shape to occur.
The distribution of sample means is defined as the set of means
from all the possible random samples of a specific size (n)
selected from a specific population.
The knowledge of the distribution comes from the central limit
theorem which says that It will be normally distributed with mean
equal to the population mean and standard deviation equal to
population SD/sqrt (n)
Shape will be very close to normal if n is greater than 30. If n<30 then it will be close to the Normal distribution but not really normal.
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