Answer:
The mean of sample (21.6) is greater than population mean and the standard deviation of sample (8.4) is also greater than population standard deviation.
Both values, mean and std are greater than corresponding population values. This means, that our sample overestimates or is skewed to the right in the values of population. Also each specific value is farther apart from the mean so variation is much bigger in our sample than in our population.
Step-by-step explanation:
To calculate the mean, we estimate the avergage of the data as
Mean = Sum(data)/n
Where n is the number of observations of sample. We have;
(25 + 32 + 16 + 12 + 11 + 38 + 22 + 21 + 19 + 20)/10 = 21.6
The standard deviation is the square root of variance. Variance is sum of the deviation of each data point to the sample mean.
Variance = sum i= 1 to n (Xi-xmean)/(n-1)
Where n = 10 the # of observations and xi is each specific data point.
If you calculate it in Excel or or by hand you obtain:
Variance = sum i= 1 to n (Xi-21.6)/(10-1) = 8.4
Both values, mean and std are greater than corresponding population values. This means, that our sample overestimates or is skewed to the right in the values of population. Also each specific value is farther apart from the mean so variation is much bigger in our sample than in our population.
