1.     Compute the mean of those 10 means.    ·         Explain how the mean of the means is equal,or not, to the...

1.     Compute the mean of those 10 means. 

·         Explain how the mean of the means is equal,or not, to the population mean of the 100 listing prices from above.

Population Mean     $30,661.74

Mean of Means       $30,661.74

The reason the means are equal, is contributed to still finding the same average for equally broke down samples. In our case, we used the average, or middle point, for 10 samples within 10 population samples. By adding these middle point values together and finding the mean, there was no mathematical change.

2.     Compute the standard deviation of those 10 means and compare the standard deviation of the 10 means to the population standard deviation of all 100 listing prices. 

·         Explain why it is significantly higher, or lower, than the population standard deviation.

Population Std. Dev.           $9,031.42

Std. Dev. of 10 Means        $8,930.17

The computed standard deviation of the 10 means is lower than that of the population of all 100 listings. This is contributed by the means not having allowed the extreme low and high values of the complete population to be considered. We only used the averages, or middle points of 10 sub-samples.

1.     Explain how much more or less the standard deviation of sample means was than the population standard deviation. According to the formula for standard deviation of sample means, it should be far less.  (That formula is σ = σ/√n  =  σ/√10  = σ/3.16  )  Does your computed σ  agree with the formula?

     According to the Empirical Rule, what percentage of your sample means should be within 1 standard deviation of the population mean?  Using your computed σ, do your sample means seem to conform to the rule?