Last name:     First name:   
          
Enter your LETTER answers HERE      
         
 1  Note:     
 2  When done, using your LAST NAME and FIRST NAME 
 3  save THIS file asE270Lastname 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 ExpenditureCase 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.
 
A9.6        
B12.8        
C14.6        
D18.1        
          
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 
 
A145.1        
B135.2        
C126.5        
D118.3        
          
3)The regression model indicates that ______% of variations in case sales is explained by media expenditure
A95.7        
B92.6        
C86.4        
D82.4        
          
4)To build a confidence interval for the slope coefficient b₁ the standard error of b₁, se(b₁) is 
A3.22        
B2.89        
C1.99        
D1.26        
          
5)To perform a test of hypothesis that the population slope parameter is zero, the test statistic t is
A6.52        
B5.63        
C4.68        
D3.89        
          
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 R0.9877      
 R Square        
 Adjusted R Square0.9695      
 Standard Error       
 Observations6      
          
 ANOVA        
  dfSSMSFSignif F   
 Regression1  160.071592.25E-04   
 Residual 184775      
 Total57579083      
          
  CoefficientsStd Errort StatP-valueLower 95%Upper 95%  
 Intercept617.662428.311.4420.2227-571.511806.84  
 X Variable 18.755  0.0002    
          
6)The percentage of the variations in cost explained by production volume is:  
A97.6%        
B93.0%        
C90.3%        
D87.7%        
          
7)The predicted total cost when production volume is 1,000 is,   
A8,581        
B8,827        
C9,373        
D9,670        
          
8)Given that the sum of the squared deviations of production volume is 96,470.83, the standard error of the slope coefficient is
 
A1.280        
B1.084        
C0.888        
D0.692        
          
9)The lower end of the 95% confidence interval for the slope coefficient is  
A5.16        
B6.83        
C8.98        
D9.49        
          
10)The value of the t Stat for the slope coefficient is    
A12.65        
B10.17        
C7.69        
D5.21        
          
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