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To determine the impact of variations in price on sales the
management of Big Bob’s Burger Barn sets different prices in its burger
joints in 75 stores located in different cities.
Using the sales and price data, a simple regression is run with sales
(in thousands of dollars) as the dependent variable and price (in
dollars) as the independent variable.
Use the following calculations and the accompanying regression summary output to answer the next seven questions.
?xy = 32847.677 x? = 5.6872
?x² = 2445.7074 y? = 77.3747
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square 0.382962612
Standard Error
Observations 75
ANOVA
df SS MS F Significance F
Regression
46.92790295 1.97E-09
Residual
Total 3115.481867
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 6.526290698 18.67832421 1.5876E-29 108.893295 134.9070522
PRICE 1.97E-09
16 The model predicts that when raising the price by $1, sales would change by $_______ thousand.
a -$7.83
b -$8.26
c -$9.04
d -$9.65
17 The predicted sales for a price of $6.00 per burger is $ _______ thousand.
a $71.4
b $74.9
c $78.6
d $82.5
18 Given that ?(y? ? y?)² = 1219.091, the sample data show that _______ fraction of variations is sales is explained by price.
a 0.68
b 0.48
c 0.39
d 0.25
19 The test statistic for the null hypothesis that a change in price has no impact on sales is:
a -6.850
b -5.798
c -4.746
d -3.694
20 The margin of error for a 95% interval estimate for the population slope parameter is:
a 4.02
b 3.34
c 2.95
d 2.28
