Question

1)

what is the difference between sample estimate and population parameter? if the sample mean of GRE test scores distribution was 90 and variance equivelent to 225 what can you say about the population distribution?

2)

if the mean score of class of 20 students in Marketing is 80 and variance is 256. calculate the coefficient of variation and provide an interpretation of the results.

Answer 1

Answer to part: 1)

Sample estimate is a statistics taken some random number from a population (whole number) which is refered as a small sample from a group/population where as population parameter is a parameter which is takes the whole population, it describes the entire population.

Variance equivqlent to 225 means Standared Deviation(SD) is 15 (square root of 225) and sample mean of GRE test score distribution is 90. A low SD means that most most of the numbers are close to the average(mean) and a high SD means that the numbers are spread out. Here mean is 90 and SD is 15 comparatively very low which emplies that population distribution is very close to the mean i.e. 90.

Answer to part: 2)

Coefficient of Variation(CV) = SD divided by Mean multiply by 100 = (SD/Mean)100

where SD = 16 (square root of 256), Mean = 80

CV = (16/80)*100 = 20

As CV comes 20 it shows the relative risk of the score scored by the students in marketing.