Assume you have weekly store-level data similar in format to the data we worked on in class. You estimate the following models using that data and get the following results...

Model A: unitsales=0+1xdisplayunitsales=0+1xdisplay

	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	1159.891	60.328	19.226	0.000
Display	183.967	23.121	7.957	0.000

Model B: unit.sales=0+1xdisplay+2xpriceunit.sales=0+1xdisplay+2xprice

	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	922.444	65.679	14.045	0.000
Display	183.967	23.121	7.957	0.000
Price	-170.339	14.847	-11.473	0.000

Given this information, all of the following statements are true EXCEPT...

Group of answer choices

the r-square for the second model (B) is higher than the first (A)

there is some non-zero correlation between display and price

there is positive correlation between display and sales

there is negative correlation between price and sales