Background InformationThe Central Limit Theorem is similar to the Law of Large Numbers. The more samples we take from ou

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Background InformationThe Central Limit Theorem is similar to
the Law of Large Numbers. The more samples we take from our sample
or the population, the closer our sample resembles a Normal
Distribution. When we look at means of samples, it happens even
more quickly! In this lab we are looking at 30 values at a time.
While the data is being pulled from a larger set, this
randomization for the initial set allows for a better change in
situation each time. The data you will be using is randomized from
90 values.The sets are:Set C1A random set of 30 individual data
values from the original list of 197 values.Set C5A random set of
30 means of groups of 5 data values from the original list of 197
values. (i.e. The mean is calculated for a set of 5 randomly
selected data values. This is repeated 30 times and those means
become your list.)Set C20Random set of 30 means of groups of 20
data values from the original list of 197 values. (i.e. The mean is
calculated for a set of 20 randomly selected data values. This is
repeated 30 times and those means become your list.)
HistogramMeanStandard DeviationSet C1HistogramMeanStandard
DeviationSet C5HistogramMeanStandard DeviationSet C20
Discussion Questions:(For each one, useone to two complete
sentences to explain what happened.)How did the shape of the
distribution of the data change, as size of the averaged set
changed?How did the mean change, as size of the averaged set
changed?How did the standard deviation change, as size of the
averaged set changed?
use desmos for your calculation