2.
The shape of the distribution with sample size 100 is very similar to the bell curve. Its
normal probability plot supports this by being linear and showing it fits the normal
distribution curve. This supports the Central Limit Theorem as the theorem states that as
the sample size increases, the sample means distributions will be similar to that of a
normal distribution. Even with the sample size of 5, its normal probability plot shows a
bit more linearity than the plot with a sample size of 2.
3.
The maximum value of web pages visited is 74. The mean is 4.667 and the standard
deviation is 6.313. The distribution is definitely not normal. There is no linearity to the
normal distribution plot and the bell curve does not match with the histogram whatsoever.
4.
The three sample means are 2.4, 4.5, and 3.1. Compared to the population mean, the
second mean is relatively close, but the first and third value are much smaller than the
mean.
5.
With the 100 sample means, the mean is 4.726 and the standard deviation is 1.903.
6.
The expected mean is 4.726 and the expected standard deviation is .602. While the mean
stays the same, the standard deviation in a sample size of 10 is smaller than the standard
![20230820_165533[14453].jpg](/doc-asset/thumb/a663539198eb01e2d7c352197e180f10296ac2db_180.jpg)
