Question

1. On top of the its own price effect on sales, Mr. Wok is also interested how the sales will change as Competitor’s price changes.

Please use data in “Linear regressions with competitor price.xsls”

• Estimate the coefficients with Mr. Work’s own price and its competitor
• How do the two prices affect the Mr. Works’s sales?

Market ID	Sales	Price	Competitor Price (Cprice)
1	228	2.2	2.2
2	216	2.7	2.9
3	223	2.4	2.4
4	207	2.9	2.6
5	216	2.8	2.4
6	247	2.2	2.5
7	233	2.0	2.2
8	249	2.3	2.7
9	239	2.1	2.4
10	209	2.7	2.4
11	214	2.8	2.4
12	236	2.6	3.0
13	218	2.6	2.1
14	191	2.9	2.2
15	223	2.6	3.0

Answer 1

Excel Results for multiple linear regression

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.899159
R Square	0.808488
Adjusted R Square	0.776569
Standard Error	7.453419
Observations	15

ANOVA
	df	SS	MS	F	Significance F
Regression	2	2814.292	1407.146	25.32959	4.93E-05
Residual	12	666.6414	55.55345
Total	14	3480.933

	Coefficients	Standard Error	t Stat	P-value
Intercept	284.8645	22.03959	12.92513	2.11E-08
Price	-46.6048	6.807572	-6.84603	1.78E-05
Competitor Price (Cprice)	22.39825	6.962266	3.217092	0.007394

The regression equation is

Sales = 284.865 - 46.605 Price + 22.398 Cprice

Increase in 1 unit of Cprice increases the sales by 22.398 units keeping Price constant.

Increase in 1 unit of Price the sales of computer decreases by 46.605 units keeping the Cprice constant.

R² = 0.8085 which means the model explains 80.85% variability in sales of computers with Price and Cprice as independent variables.