E270 Online Test 7
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Last name: | First name: | ||||||||
Enter your LETTER answers HERE | |||||||||
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1 | Note: | ||||||||
2 | When done, using your LAST NAME and FIRST NAME | ||||||||
3 | save THIS file as | E270Lastname Firstname TEST7 | |||||||
4 | and e-mail it to | [email protected] | |||||||
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Next 5 questions are based on the following data relating cases sold of the brand of soft drink to media expenditure. | |||||||||
Media Expenditure | Case Sales | ||||||||
($millions) | (millions) | Use the following calculations in the relevant formulas to answer the questions | |||||||
65 | 980 | ||||||||
46 | 960 | n = | 7 | ||||||
32 | 700 | x̅ = | 32 | ||||||
28 | 345 | y̅ = | 520 | ||||||
25 | 360 | ∑xy = | 153,310 | ∑(y − y̅)² = | 773,450 | ||||
18 | 180 | ∑x² = | 9,198 | ∑(y − ŷ)² = | 105,248.57 | ||||
10 | 115 | ∑(x − x̅)² = | 2,030 | ∑(ŷ − y̅)² = | 668,201.43 | ||||
1) | The estimated regression equation predicts that for each additional $1 million in media expenditure, the case sales would increase by ______ million. | ||||||||
A | 9.6 | ||||||||
B | 12.8 | ||||||||
C | 14.6 | ||||||||
D | 18.1 | ||||||||
2) | The regression model shows that on average observed values of Case Sales deviate from the predicted values (or from the regression line) by ______ million cases | ||||||||
A | 145.1 | ||||||||
B | 135.2 | ||||||||
C | 126.5 | ||||||||
D | 118.3 | ||||||||
3) | The regression model indicates that ______% of variations in case sales is explained by media expenditure | ||||||||
A | 95.7 | ||||||||
B | 92.6 | ||||||||
C | 86.4 | ||||||||
D | 82.4 | ||||||||
4) | To build a confidence interval for the slope coefficient b₁ the standard error of b₁, se(b₁) is | ||||||||
A | 3.22 | ||||||||
B | 2.89 | ||||||||
C | 1.99 | ||||||||
D | 1.26 | ||||||||
5) | To perform a test of hypothesis that the population slope parameter is zero, the test statistic t is | ||||||||
A | 6.52 | ||||||||
B | 5.63 | ||||||||
C | 4.68 | ||||||||
D | 3.89 | ||||||||
Use the following Excel regression output to answer the next 5 questions. The output shows the result of running a regression relating costs to production volume. Fill in the highlighted cells first. | |||||||||
SUMMARY OUTPUT | |||||||||
Regression Statistics | |||||||||
Multiple R | 0.9877 | ||||||||
R Square | |||||||||
Adjusted R Square | 0.9695 | ||||||||
Standard Error | |||||||||
Observations | 6 | ||||||||
ANOVA | |||||||||
df | SS | MS | F | Signif F | |||||
Regression | 1 | 160.07159 | 2.25E-04 | ||||||
Residual | 184775 | ||||||||
Total | 5 | 7579083 | |||||||
Coefficients | Std Error | t Stat | P-value | Lower 95% | Upper 95% | ||||
Intercept | 617.662 | 428.31 | 1.442 | 0.2227 | -571.51 | 1806.84 | |||
X Variable 1 | 8.755 | 0.0002 | |||||||
6) | The percentage of the variations in cost explained by production volume is: | ||||||||
A | 97.6% | ||||||||
B | 93.0% | ||||||||
C | 90.3% | ||||||||
D | 87.7% | ||||||||
7) | The predicted total cost when production volume is 1,000 is, | ||||||||
A | 8,581 | ||||||||
B | 8,827 | ||||||||
C | 9,373 | ||||||||
D | 9,670 | ||||||||
8) | Given that the sum of the squared deviations of production volume is 96,470.83, the standard error of the slope coefficient is | ||||||||
A | 1.280 | ||||||||
B | 1.084 | ||||||||
C | 0.888 | ||||||||
D | 0.692 | ||||||||
9) | The lower end of the 95% confidence interval for the slope coefficient is | ||||||||
A | 5.16 | ||||||||
B | 6.83 | ||||||||
C | 8.98 | ||||||||
D | 9.49 | ||||||||
10) | The value of the t Stat for the slope coefficient is | ||||||||
A | 12.65 | ||||||||
B | 10.17 | ||||||||
C | 7.69 | ||||||||
D | 5.21 | ||||||||
- 9 years ago
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