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?