A company specializing in home decoration items would like to build a regression model consisting of 5 factors to predict sales. Data for the past 24 months on sales and 5 factors were collected for one particular home decoration item and the SPSS package was used to get the output. The relevant outputs are given below in Tables 1 and 2. The variables for which the data has been collected are as follows Dependent variable Y = monthly sales in lakhs (for one particular home decoration item) Independent variables 1)advertising cost in lakhs 2)competition index 3)number of existing customers 4) number of dealer outlets 5) number of personnel delivering to the customer The company decided to follow Stepwise Multiple Linear Regression. Read the output data given below and answer the questions given Table 1 Multiple R 0.965 R square 0.931 Adjusted R square 0.895 Standard Error 4.235 From the ANOVA table, the extracted P value is 0.001 Table 2 Variable Beta SE B B t Sig t Advertisement 0.1634 1.3054 .7982 .537 0.476 competition 0.0034 2.123 0.0667 0.03 0.987 customers 0.187 0.298 0.453 0.65 0.576 Dealer outlets 0.654 0.628 1.465 2.78 0.0298 Delivery personnel 0.189 .908 0.987 1.987 0.032 Constant 34.67 5.987 0.198 .897 Answer the questions 1) What is the significance of R square 2) What is the importance of adjusted R square? 3) Form the regression equation 4) Are all independent variables important? Justify your answer 5) Predict sales if given the following advertisement expenditure is 50 lakhs, competition index is 3, existing customers are 80, dealer outlets are 103, delivery personnel is 32.
A company specializing in home decoration items would like to build a regression model consisting of 5 factors to predict sales. Data for the past 24 months on sales and 5 factors were collected for one particular home decoration item and the SPSS package was used to get the output. The relevant outputs are given below in Tables 1 and 2.
The variables for which the data has been collected are as follows
Dependent variable
Y = monthly sales in lakhs (for one particular home decoration item)
Independent variables
1)advertising cost in lakhs
2)competition index
3)number of existing customers
4) number of dealer outlets
5) number of personnel delivering to the customer
The company decided to follow Stepwise Multiple Linear Regression.
Read the output data given below and answer the questions given
Table 1
|
Multiple R |
0.965 |
|
R square |
0.931 |
|
Adjusted R square |
0.895 |
|
Standard Error |
4.235 |
From the ANOVA table, the extracted P value is 0.001
Table 2
|
Variable |
Beta |
SE B |
B |
t |
Sig t |
|
Advertisement |
0.1634 |
1.3054 |
.7982 |
.537 |
0.476 |
|
competition |
0.0034 |
2.123 |
0.0667 |
0.03 |
0.987 |
|
customers |
0.187 |
0.298 |
0.453 |
0.65 |
0.576 |
|
Dealer outlets |
0.654 |
0.628 |
1.465 |
2.78 |
0.0298 |
|
Delivery personnel |
0.189 |
.908 |
0.987 |
1.987 |
0.032 |
|
Constant |
|
34.67 |
5.987 |
0.198 |
.897 |
Answer the questions
1) What is the significance of R square
2) What is the importance of adjusted R square?
3) Form the regression equation
4) Are all independent variables important? Justify your answer
5) Predict sales if given the following advertisement expenditure is 50 lakhs, competition index is 3, existing customers are 80, dealer outlets are 103, delivery personnel is 32.
Step by step
Solved in 4 steps
