Consider a linear demand model to explain the quantity demanded for a product: where Q = quantity sold, Price = price of the product, Income = purchaser’s income, Advert = advertising. The following data was collected in year 2018. The company spends millions of money in advertisements. The company wants to know how advertisement as well how other factors affect the quantity of units sold. The results are as follows: Model Summary R 0.986 R2 0.973 Standard error of estimate 6.9872 Variables Coefficient Std error Sig Constant 205.862 19.354 0.000 Price -12.242 1.407 0.000 Income 1.414 0.422 0.015 Advert -3,344 1.798 0.112 Interpret and write a report based on the results obtained above.
Consider a linear
where Q = quantity sold,
The results are as follows:
|
Model Summary |
||||
|
R |
0.986 |
|||
|
R2 |
0.973 |
|||
|
Standard error of estimate |
6.9872 |
|||
|
Variables |
Coefficient |
Std error |
Sig |
|
|
Constant |
205.862 |
19.354 |
0.000 |
|
|
Price |
-12.242 |
1.407 |
0.000 |
|
|
Income |
1.414 |
0.422 |
0.015 |
|
|
Advert |
-3,344 |
1.798 |
0.112 |
|
Interpret and write a report based on the results obtained above.
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