The tables below are the results of the following linear regression models using Price Promotion data. 'ln' in front of a variable means natural log (base e).

QuantX: Total number of liquid ounces sold for brand X

QuantY: Total number of liquid ounces sold for brand Y

PriceX: The retail price per liquid ounce for brand X in dollars

PriceY: The retail price per liquid ounce for brand Y in dollars

DealX: Indicator of whether brand X was price-promoted

DealY: Indicator of whether brand Y was price-promoted

FeatX: Indicator of whether brand X was advertised or put on in-store display

FeatY: Indicator of whether brand Y was advertised or put on in-store display

M1: lnQuantY = a₀ + a₁ lnPriceY + a₂ lnPriceX + a₃ FeatY + a₄ DealY

	Coef.	p
lnPriceY	-2.3	0.001
lnPriceX	0.56	0.009
FeatY	1.53	0.011
DealY	0.69	0.002
Constant	1.54	0.031

M2: QuantY = b₀ + b₁ PriceY + b₂ FeatY + b₃ DealY

	Coef.	p
PriceY	-259385	0.03
FeatY	13691	0.021
DealY	16959	0.3005
Constant	10026	0.013

M3: QuantX = c₀ + c₁ PriceX + c₂ FeatX + c₃ DealX

	Coef.	p
PriceX	-132563	0.034
FeatX	11642	0.001
DealX	13473	0.022
Constant	15322	0.015

12. Which one is NOT correct?

Group of answer choices

Demand for Y is elastic.

The demand curve for Y will be relatively flat

A price increase in Y will increase the total revenue of Y

Brand X and Y are substitutes