A marketing manager is studying the relationship between the sales and various m
ID: 3313715 • Letter: A
Question
A marketing manager is studying the relationship between the sales and various marketing expenditures to determine the most successful techniques in the company’s marketing mix. Analysis of the data produced the following multivariate regression output (in thousands $$):
Unstandardized coefficients
B
St. Error
Sig.
(Constant)
800.2
108.633
0.415
TV advertising expenditures
0.22
0.996
0.000
Print advertising expenditures
-0.15
9.828
0.000
Promotional expenditures
2.7
3.609
0.001
Social media marketing expenditures
0.17
0.554
0.031
R²=0.61
1. Write down the regression equation. What seems to be the effect of each independent variable on the dependent variable? Based on this analysis, what is the most successful technique in the company’s marketing mix? How much will $1 increase in expenditures for this technique affect sales?
2. How strong is the relationship between the variables? What is the explanatory power of the model? How can you interpret this?
Unstandardized coefficients
B
St. Error
Sig.
(Constant)
800.2
108.633
0.415
TV advertising expenditures
0.22
0.996
0.000
Print advertising expenditures
-0.15
9.828
0.000
Promotional expenditures
2.7
3.609
0.001
Social media marketing expenditures
0.17
0.554
0.031
Explanation / Answer
Asnwer-
the regression equation is
sales = B0 + b1*TV advertising expenditures+b2*Print advertising expenditures+b3*Promotional expenditures+b4*Social media marketing expenditures + e ...............................model
effect of independent variables
intercept- is in significant , so there is no offect, this model ie qithou intercept model
TV advertising expenditures- p- value is significant
Print advertising expenditures- variable is significant and it is giving the negative effect on sales
Promotional expenditures- p- value is significant, and it has +effect
Social media marketing expenditures- the variable showing the insignificant contribution in model
sales = b1*TV advertising expenditures+b2*Print advertising expenditures+b3*Promotional expenditures+ e ...............................model
this is the best signifiant model for the prediction of salse
2) the R-square =0.61
it shows that the 0.61% variablilty is showing by the independent variable
thanks
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