Question

The standard errors for regression model, Y   =   9.154976   - 2.76802X1   + 1.666692X2   + 0.492742X3   - 0.43956DA   - 0.17007DB

are shown in the table below

Y	=	9.154976	- 2.76802X1	+ 1.666692X2	+ 0.492742X3	- 0.43956DA	- 0.17007DB	R2=0.959727
Std Error		(1.59)	(0.41)	(0.19)	(0.08)	(0.07)	(0.07)	Ra2=0.951337
Diff		7.565	2.358	1.257	0.412	0.3695	0.1	F=114.3862

Where:

• Y = Bottles of detergent demanded, in hundreds of thousands of bottles
• X1 = Company's price of Detergent in dollars
• X2 = Average Industry Price in dollars
• X3 = Company's advertising spending in hundreds of thousands of dollars
• DA = TV Advertising Campaign
• DB = Balanced mix of TV and Radio ads

QUESTION: Write conclusive statements for each variable for this model. X1 variable is stated here below as an example:

• Answer for X1: When the Company’s Price of Detergent rises by $1, the sales of detergent falls by 2.3578 since coefficient is negative
• Please provide answers for all other terms.

Answer 1

For X2:

When the Average Industry Price rises by $1, the sales of detergent increases by 1.257 since coefficient is positive.

For X3:

When the Company's advertising spending rises by $100,000, the sales of detergent increases by 0.412 since coefficient is positive.

For DA:

When the Company’s TV Advertising campaign rises by 1 unit, the sales of detergent falls by 0.3695 since coefficient is negative.

For DB:

When the Company’s Balanced mix of TV and Radio ads rises by 1 unit, the sales of detergent falls by 0.1 since coefficient is negative.