The following is the linear specification of demand for a good, where there are only two of these businesses in the area

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The following is the linear specification of demand for a good,
where there are only two of these businesses in the area and the
number of buyers, N, of the good did not change during the
specified time period. Q = a + bPRICE + cINCOME + dSubPrice +
eComPrice where Q = sales of the good for firm 1 PRICE = price of
the good for firm 1 INCOME = average annual household income in the
area SubPrice = price of the substitute good for firm 1 ComPrice =
price of the complementary good for firm 1 The estimation of the
above equation yielded the following output. SUMMARY OUTPUT
Regression Statistics Multiple R 0.97164 R Square 0.944084 Adjusted
R Square 0.932312 Standard Error 47.218 Observations 24 ANOVA df SS
MS F Significance F Regression 4 715222.1 178805.5 80.19841
1.26E-11 Residual 19 42361.25 2229.54 Total 23 757583.3
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Lower 95.0% Upper 95.0% Intercept 1066.168 721.4397 1.477834
0.155838 -443.823 2576.159 -443.823 2576.159 PRICE -227.865
14.92088 -15.2716 4.01E-12 -259.095 -196.636 -259.095 -196.636
INCOME 0.099456 0.014024 7.091955 9.56E-07 0.070104 0.128808
0.070104 0.128808 SubPrice 104.151 57.93111 1.797843 0.088113
-17.1002 225.4022 -17.1002 225.4022 ComPrice 67.54289 29.3017
2.305084 0.032611 6.213721 128.8721 6.213721 128.8721
1. If the number of residents had not been constant, would this
variable have affected the model? If yes, how? If no, why not?
2. What is the equation of the sample regression line?
3. Use the p-value for the F statistic to test to see if the
model as a whole is statistically significant at the 1 percent
level of significance. Show all of your work.
4. Use the p-values for the parameter estimates to test to see
if the four estimated slope parameters are statistically
significant at the 1 percent level of significance. Show all of
your work.
5. What is the interpretation of coefficients b, c, d, and
e?
6. What percent of the total variation in the good’s sales is
explained by the model? From where did you get this
information?
7. If PRICE = INCOME = SubPrice = ComPrice = 0, what is the
value of SALES? Show all of your work.
8. What value do you predict SALES will take if PRICE = $9.10,
INCOME = $26,700, SubPrice = $10.50 and ComPrice =$1.20?
9. Using the information in 8, compute price elasticity of
demand, income elasticity of demand, and the two cross-price
elasticities of demand.
10. What do the elasticities in 9 indicate about elasticity of
demand for the good, the impact of income on the sale of the good
and the type of good, the impact of the cross-price elasticity of
SubPrice on the sale of the good, and the cross-price elasticity of
ComPrice on the good?