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Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:   Month Machine Hours Electricity Costs January 2,500 $ 18,400   February 2,900   21,000   March 1,900   13,500   April 3,100   23,000   May 3,800   28,250   June 3,300   22,000   July 4,100   24,750   August 3,500   22,750   September 2,000   15,500   October 3,700   26,000   November 4,700   31,000   December 4,200   27,750        Summary Output Regression Statistics Multiple R 0.965 R Square 0.932 Adjusted R2 0.925 Standard Error 1,425.18 Observations 12.00     Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 3,726.88 1,682.82 2.21 0.05 (22.69) 7,476.45 Machine Hours 5.77 0.49 11.7 0.00 4.67 6.87   The percent of the total variance that can be explained by the regression is:   Multiple Choice   98.2%.   93.2%.   92.5%.   96.5%.

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:   Month Machine Hours Electricity Costs January 2,500 $ 18,400   February 2,900   21,000   March 1,900   13,500   April 3,100   23,000   May 3,800   28,250   June 3,300   22,000   July 4,100   24,750   August 3,500   22,750   September 2,000   15,500   October 3,700   26,000   November 4,700   31,000   December 4,200   27,750        Summary Output Regression Statistics Multiple R 0.965 R Square 0.932 Adjusted R2 0.925 Standard Error 1,425.18 Observations 12.00     Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 3,726.88 1,682.82 2.21 0.05 (22.69) 7,476.45 Machine Hours 5.77 0.49 11.7 0.00 4.67 6.87   The percent of the total variance that can be explained by the regression is:   Multiple Choice   98.2%.   93.2%.   92.5%.   96.5%.

Principles of Cost Accounting
Principles of Cost Accounting
17th Edition
ISBN:9781305087408
Author:Edward J. Vanderbeck, Maria R. Mitchell
Publisher:Edward J. Vanderbeck, Maria R. Mitchell
Chapter4: Accounting For Factory Overhead
Section: Chapter Questions
Problem 4P: Using the data in P4-2 and Microsoft Excel: 1. Separate the variable and fixed elements. 2....
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Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
  

Month Machine Hours Electricity Costs
January 2,500 $ 18,400  
February 2,900   21,000  
March 1,900   13,500  
April 3,100   23,000  
May 3,800   28,250  
June 3,300   22,000  
July 4,100   24,750  
August 3,500   22,750  
September 2,000   15,500  
October 3,700   26,000  
November 4,700   31,000  
December 4,200   27,750  
 

  

Summary Output
Regression Statistics
Multiple R 0.965
R Square 0.932
Adjusted R2 0.925
Standard Error 1,425.18
Observations 12.00

 

  Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 3,726.88 1,682.82 2.21 0.05 (22.69) 7,476.45
Machine Hours 5.77 0.49 11.7 0.00 4.67 6.87

  
The percent of the total variance that can be explained by the regression is:

 

Multiple Choice
  •  

    98.2%.

  •  
    93.2%.
  •  

    92.5%.

  •  

    96.5%.

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