II. Let us see what you have learned in this module by
completing the following statements.
The Central Limit Theorem implies the following important
ideas in statistics:
1. The sample mean can be considered approximately
normally distributed if the sample size is
2. If the population is not normally distributed, or if we don't
know of its distribution, the
allows us to
conclude that the distribution of the sample mean will be
normal if the sample size is sufficiently large.
3. The population mean is equal to the
of the
sampling distribution. That is u = ur.
4. Mean of the sampling distribution of the sample mean is
equal to the population mean: H. - = H and the
of the sampling distribution of the sample
mean (sampling with replacement)
is equal to: 0,7
5. The Central Limit Theorem describes the
of the sample mean taken from a
population that is not normally distributed
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