monsieuruzairo3
Member
Dear David,
Please note the following question. I have doubts on the options. I believe the question is flawed as incomplete information is given. Kindly confim
Kris, FRM® is analyzing the sales growth of a Two Wheelers launched two years ago Suzuki. Majorly 3 factors contributes to sales growth and following are the results:
Y = b + 1.6 X1 + 1.3 X2 + 4 X3
Sum of Squared Regression [SSR] = 880.5
Sum of Squared Errors [SEE = 25.5
Determine what proportion of sales growth is explained by the regression results.
A. 0.36
B. 0.98
C. 0.64
D. 0.56
Now If we take Sum of Squared errors and ignore SEE then R^2 = 880.5/Sum(880.5,25.5)
However if we assume that this is SEE and not Sum of squared errors then
N=24(2 years), K=3
SEE=sqrt(SSE/n-k-1)
25.5=sqrt(SSE/20)
SSE=13005
TSS=13005+880.5=13885.5
R^2 = 880.5/13885.5 = .0634 which doesnt match any of the option
Answer provided is D 0.56. Can you please explain how this is?
Best uzi
Please note the following question. I have doubts on the options. I believe the question is flawed as incomplete information is given. Kindly confim
Kris, FRM® is analyzing the sales growth of a Two Wheelers launched two years ago Suzuki. Majorly 3 factors contributes to sales growth and following are the results:
Y = b + 1.6 X1 + 1.3 X2 + 4 X3
Sum of Squared Regression [SSR] = 880.5
Sum of Squared Errors [SEE = 25.5
Determine what proportion of sales growth is explained by the regression results.
A. 0.36
B. 0.98
C. 0.64
D. 0.56
Now If we take Sum of Squared errors and ignore SEE then R^2 = 880.5/Sum(880.5,25.5)
However if we assume that this is SEE and not Sum of squared errors then
N=24(2 years), K=3
SEE=sqrt(SSE/n-k-1)
25.5=sqrt(SSE/20)
SSE=13005
TSS=13005+880.5=13885.5
R^2 = 880.5/13885.5 = .0634 which doesnt match any of the option
Answer provided is D 0.56. Can you please explain how this is?
Best uzi