Why is the standard deviation of the distribution of sample means smaller than the standard deviation of the population from which it came? Select all that apply. O According to the central limit theorem, we divide the population standard deviation o by the square root of the sample size n, so as n gets bigger the quotient gets smaller. O Since we are only graphing the averages of the samples, extremes like the minimum and maximum of each sample are not present, making the standard deviation of the sample means smaller than the standard deviation of the population. O The standard deviation of the distribution of sample means is smaller than the standard deviation of the population because a sample is always small than the population.
Why is the standard deviation of the distribution of sample means smaller than the standard deviation of the population from which it came? Select all that apply. O According to the central limit theorem, we divide the population standard deviation o by the square root of the sample size n, so as n gets bigger the quotient gets smaller. O Since we are only graphing the averages of the samples, extremes like the minimum and maximum of each sample are not present, making the standard deviation of the sample means smaller than the standard deviation of the population. O The standard deviation of the distribution of sample means is smaller than the standard deviation of the population because a sample is always small than the population.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Why is the standard deviation of the distribution of sample means smaller than the standard deviation of
the population from which it came?
Select all that apply.
O According to the central limit theorem, we divide the population standard deviation o by the square
root of the sample size n, so as n gets bigger the quotient gets smaller.
O Since we are only graphing the averages of the samples, extremes like the minimum and maximum of
each sample are not present, making the standard deviation of the sample means smaller than the
standard deviation of the population.
O The standard deviation of the distribution of sample means is smaller than the standard deviation of
the population because a sample is always small than the population.
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