In the options we can see there are 2 answers that are false, that being “There is no correlation” and “sales revenue will increase by 85% more than advertising expenditure”. the first one is false because r = 0.85 which is a good correlation, and the second because .85 is the correlation coefficient and not the coefficient of the variable in y=a+bx.

the answer is therefore about how much of the variation in sales revenue is explained by the variation in advertising expenditure, ie, they are asking you to calculate the coefficient of determination.

that value is r squared, .85 squared is .722 which is also 72%

The coefficient of variation is the square of the correlation coefficient, and it measures what % of variations in one variable can be explained by variations in the other variable.

I do explain this in my free lectures – did you watch the lectures before attempting the test?

Alber says

This set of exercises is quite awesome

Iveytee says

Sir #5 the highest is $75,000 and 2,500 units, the lowest $69,500 and 1,500 units. Therefore the answer should be

Total cost = $61,250 + 5.50 x quantity

John Moffat says

No. As I make clear in my lectures, you use the highest and lowest levels of production (not the highest and lowest costs).

MuhammedSaleem says

sir, the formulas will be given in the exam know?

but here it doesnt…

John Moffat says

This is a quick test and is not the exam. The formula sheet is printed in our lecture notes.

MuhammedSaleem says

okkkk

gkumar84@live.com says

In question 3, there is no mention of Coefficient determination but why the explanation includes determination?

Please can someone advise?

kamo7293 says

In the options we can see there are 2 answers that are false, that being “There is no correlation” and “sales revenue will increase by 85% more than advertising expenditure”. the first one is false because r = 0.85 which is a good correlation, and the second because .85 is the correlation coefficient and not the coefficient of the variable in y=a+bx.

the answer is therefore about how much of the variation in sales revenue is explained by the variation in advertising expenditure, ie, they are asking you to calculate the coefficient of determination.

that value is r squared, .85 squared is .722 which is also 72%

bambiiii says

how did you get 11 as n (from question #1)?

Rose17mary says

The information provided before the question says we have 11 pairs of data hence n=11

dalesp8 says

Hello John,

Can I just say that this topic was explain really well. Thank you

John Moffat says

Thank you for your comment 馃檪

TEBOH10 says

Sir I don’t understand why on question 3 was I supposed to be using r虏 (coefficient of determination)

John Moffat says

Because the correct statement is how the coefficient of determination is defined, as I state in my lectures.

AnoTae says

Good day madam/sir

Can you please explain me question #3?

John Moffat says

The coefficient of variation is the square of the correlation coefficient, and it measures what % of variations in one variable can be explained by variations in the other variable.

I do explain this in my free lectures – did you watch the lectures before attempting the test?

mariamohi says

100% 馃檪

Rose17mary says

??Samee

Gabriel says

Question #5 for the high low method, the highest level is 75000 not 74000. If 74000 is being used, can you kindly explain why.

thank you.

John Moffat says

We use the highest and lowest of the independent variable which here is the production units. I do explain this in my free lecture.

Gabriel says

Good Day Sir,

can you kindly elaborate a little more on question #2.

John Moffat says

But what do you want me to elaborate? As the answer says, the coefficient must lie between +1 and -1 (which 1.4 does not).

Again, I explain this in my free lectures – did you not watch the lectures before attempting the test?