Use these regression results for all of the questions.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.996580178
R Square	0.993172052
Adjusted R Square	0.99154635
Standard Error	17.65887216
Observations	27
ANOVA
	df	SS	MS	F	Significance F
Regression	5	952531.8008	190506.3602	610.9188905	5.45944E-22
Residual	21	6548.551085	311.835766
Total	26	959080.3519
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 90.0%	Upper 90.0%
Intercept	-18.89004058	30.17276876	-0.626062551	0.538019899	-81.63774823	43.85766707	-70.80961828	33.02953712
Store size (sq ft)	16.19810642	3.546095704	4.56787063	0.000167222	8.823596696	23.57261614	10.0961874	22.30002543
Inventory in ($)	0.174560026	0.05764254	3.028319481	0.00639381	0.054685802	0.294434249	0.075372035	0.273748016
Ad Spending ($)	11.53854332	2.535360595	4.551046248	0.00017407	6.265972329	16.81111432	7.175839574	15.90124707
# families	13.58115172	1.771782398	7.665248133	1.62285E-07	9.896528512	17.26577492	10.53236973	16.6299337
# of competing stores	-5.31056871	1.706561037	-3.111853953	0.005276862	-8.85955667	-1.76158075	-8.247121503	-2.374015917

1. Is the coefficient on ad spending significant at the 0.05 significance level? Why?

Yes, because the p-value is greater than 0.05

No, because the p-value is greater than 0.05

No, because the p-value is less than 0.05

Yes, because the p-value is less than 0.05

2. Which is the correct model?

Sales = 0.99+0.99(store size)+17.66(inventory)+27(ad spending)+5(# of families)+43.86(# of competing stores)

Sales = 30.17+3.55(store size)+0.06(inventory)+2.54(ad spending)+1.77(# of families)+1.71(# of competing stores)

Sales = -18.89+30.17(standard error)-0.62(t-stat)+0.54(p-value)

Sales = -18.89+16.20(store size)+0.17(inventory)+11.54(ad spending)+13.58(# of families)-5.31(# of competing stores)

3. What is the impact of more competing stores?

Sales will go down.

Sales will go up.

Sales will stay the same.

4. If they increased store size by 100 square feet, how much would sales go up?

$3546

$4568

$0.16

$1620

5. If they increased inventory by $1000, how much would sales change?

Go down by 99%

Go up by 99%

Go up by $175

Go down by $175