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book Fundamentals of Cost Accounting 3rd Edition by William N. Lanen, Shannon W. Anderson, Michael Maher cover

Fundamentals of Cost Accounting 3rd Edition by William N. Lanen, Shannon W. Anderson, Michael Maher

Edition 3ISBN: 0073527114
book Fundamentals of Cost Accounting 3rd Edition by William N. Lanen, Shannon W. Anderson, Michael Maher cover

Fundamentals of Cost Accounting 3rd Edition by William N. Lanen, Shannon W. Anderson, Michael Maher

Edition 3ISBN: 0073527114
Exercise 45

Interpretation of Regression Results: Multiple Choice

The Business School at Eastern College is collecting data as a first step in the preparation of next year’s budget. One cost that is being looked at closely is administrative staff as a function of student credit hours. Data on administrative costs and credit hours for the most recent 13 months follow:

Month

Administrative Costs

Credit Hours

July

$ 543,064

525

August

346,975

242

September

960,036

2,923

October

908,855

2,100

November

1,084,705

2,749

December

774,686

2,335

January

920,375

2,812

February

1,029,000

2,883

March

880,496

2,234

April

806,085

2,358

May

1,049,908

2,856

June

715,756

882

July

538,301

662

Total

$10,558,242

25,561

Average

$ 812,172

1,966

The controller’s office has analyzed the data and given you the results from the regression analysis:

 <span class=bold>Interpretation of Regression Results: Multiple Choice</span> The Business School at Eastern College is collecting data as a first step in the preparation of next year’s budget. One cost that is being looked at closely is administrative staff as a function of student credit hours. Data on administrative costs and credit hours for the most recent 13 months follow: <table cellspacing=0 cellpadding=0 border=1>    <tbody>     <tr>      <td valign=top> Month </td>      <td valign=top align=right><p align=right>Administrative Costs </td>      <td valign=top align=right><p align=right>Credit Hours </td>     </tr>     <tr>      <td valign=top> July </td>      <td valign=top align=right><p align=right>$ 543,064 </td>      <td valign=top align=right><p align=right>525 </td>     </tr>     <tr>      <td valign=top> August </td>      <td valign=top align=right><p align=right>346,975 </td>      <td valign=top align=right><p align=right>242 </td>     </tr>     <tr>      <td valign=top> September </td>      <td valign=top align=right><p align=right>960,036 </td>      <td valign=top align=right><p align=right>2,923 </td>     </tr>     <tr>      <td valign=top> October </td>      <td valign=top align=right><p align=right>908,855 </td>      <td valign=top align=right><p align=right>2,100 </td>     </tr>     <tr>      <td valign=top> November </td>      <td valign=top align=right><p align=right>1,084,705 </td>      <td valign=top align=right><p align=right>2,749 </td>     </tr>     <tr>      <td valign=top> December </td>      <td valign=top align=right><p align=right>774,686 </td>      <td valign=top align=right><p align=right>2,335 </td>     </tr>     <tr>      <td valign=top> January </td>      <td valign=top align=right><p align=right>920,375 </td>      <td valign=top align=right><p align=right>2,812 </td>     </tr>     <tr>      <td valign=top> February </td>      <td valign=top align=right><p align=right>1,029,000 </td>      <td valign=top align=right><p align=right>2,883 </td>     </tr>     <tr>      <td valign=top> March </td>      <td valign=top align=right><p align=right>880,496 </td>      <td valign=top align=right><p align=right>2,234 </td>     </tr>     <tr>      <td valign=top> April </td>      <td valign=top align=right><p align=right>806,085 </td>      <td valign=top align=right><p align=right>2,358 </td>     </tr>     <tr>      <td valign=top> May </td>      <td valign=top align=right><p align=right>1,049,908 </td>      <td valign=top align=right><p align=right>2,856 </td>     </tr>     <tr>      <td valign=top> June </td>      <td valign=top align=right><p align=right>715,756 </td>      <td valign=top align=right><p align=right>882 </td>     </tr>     <tr>      <td valign=top> July </td>      <td valign=top align=right><p align=right><span class=underline>538,301</span> </td>      <td valign=top align=right><p align=right><span class=underline>662</span> </td>     </tr>     <tr>      <td valign=top> Total </td>      <td valign=top align=right><p align=right><span class=underline>$10,558,242</span> </td>      <td valign=top align=right><p align=right><span class=underline>25,561</span> </td>     </tr>     <tr>      <td valign=top> Average </td>      <td valign=top align=right><p align=right><span class=underline>$ 812,172</span> </td>      <td valign=top align=right><p align=right><span class=underline>1,966</span> </td>     </tr>    </tbody>   </table> The controller’s office has analyzed the data and given you the results from the regression analysis:   <span class=bold><span class=italics>Required</span></span> <span class=italics>a.</span> In the standard regression equation <span class=italics>y = a + bx,</span> the letter <span class=italics>b</span> is best described as the (1) Independent variable. (2) Dependent variable. (3) Constant coefficient. (4) Correlation coefficient. (5) Variable cost coefficient. <span class=italics>b.</span> In the standard regression equation <span class=italics>y = a + bx,</span> the letter <span class=italics>y</span> is best described as the (1) Independent variable. (2) Correlation coefficient. (3) Constant coefficient. (4) Variable cost coefficient. (5) Dependent variable. <span class=italics>c.</span> In the standard regression equation <span class=italics>y = a + bx,</span> the letter <span class=italics>x</span> is best described as the (1) Independent variable. (2) Dependent variable. (3) Constant coefficient. (4) Variable cost coefficient. (5) Correlation coefficient. <span class=italics>d.</span> If the controller uses the high-low method to estimate costs, the cost equation for administrative costs is (numbers are rounded to the nearest dollar) (1) Cost = $291,637 + 229 × Credit hours. (2) Cost = $233,571 + 101 × Credit hours. (3) Cost = $229.50 × Credit hours. (4) Cost = $404,874. (5) Some other equation. <span class=italics>e.</span> Based on the results of the controller’s regression analysis, the estimate of administrative costs in a month with 2,100 credit hours would be (1) $834,993. (2) $844,200. (3) $404,917. (4) $839,575. (5) Some other amount. <span class=italics>f.</span> The correlation coefficient (rounded) for the regression equation for administrative costs is (1) 0.871. (2) 0.933. (3) 0.859. (4)   (5) Some other amount. <span class=italics>g.</span> The percent of the total variance (rounded) that can be explained by the regression is (1) 85.9. (2) 87.1. (3) 93.3. (4) 96.6. (5) Some other amount.

Required

a. In the standard regression equation y = a + bx, the letter b is best described as the

(1) Independent variable.

(2) Dependent variable.

(3) Constant coefficient.

(4) Correlation coefficient.

(5) Variable cost coefficient.


b. In the standard regression equation y = a + bx, the letter y is best described as the

(1) Independent variable.

(2) Correlation coefficient.

(3) Constant coefficient.

(4) Variable cost coefficient.

(5) Dependent variable.


c. In the standard regression equation y = a + bx, the letter x is best described as the

(1) Independent variable.

(2) Dependent variable.

(3) Constant coefficient.

(4) Variable cost coefficient.

(5) Correlation coefficient.


d. If the controller uses the high-low method to estimate costs, the cost equation for administrative costs is (numbers are rounded to the nearest dollar)

(1) Cost = $291,637 + 229 × Credit hours.

(2) Cost = $233,571 + 101 × Credit hours.

(3) Cost = $229.50 × Credit hours.

(4) Cost = $404,874.

(5) Some other equation.


e. Based on the results of the controller’s regression analysis, the estimate of administrative costs in a month with 2,100 credit hours would be

(1) $834,993.

(2) $844,200.

(3) $404,917.

(4) $839,575.

(5) Some other amount.


f. The correlation coefficient (rounded) for the regression equation for administrative costs is

(1) 0.871.

(2) 0.933.

(3) 0.859.

(4)  <span class=bold>Interpretation of Regression Results: Multiple Choice</span> The Business School at Eastern College is collecting data as a first step in the preparation of next year’s budget. One cost that is being looked at closely is administrative staff as a function of student credit hours. Data on administrative costs and credit hours for the most recent 13 months follow: <table cellspacing=0 cellpadding=0 border=1>    <tbody>     <tr>      <td valign=top> Month </td>      <td valign=top align=right><p align=right>Administrative Costs </td>      <td valign=top align=right><p align=right>Credit Hours </td>     </tr>     <tr>      <td valign=top> July </td>      <td valign=top align=right><p align=right>$ 543,064 </td>      <td valign=top align=right><p align=right>525 </td>     </tr>     <tr>      <td valign=top> August </td>      <td valign=top align=right><p align=right>346,975 </td>      <td valign=top align=right><p align=right>242 </td>     </tr>     <tr>      <td valign=top> September </td>      <td valign=top align=right><p align=right>960,036 </td>      <td valign=top align=right><p align=right>2,923 </td>     </tr>     <tr>      <td valign=top> October </td>      <td valign=top align=right><p align=right>908,855 </td>      <td valign=top align=right><p align=right>2,100 </td>     </tr>     <tr>      <td valign=top> November </td>      <td valign=top align=right><p align=right>1,084,705 </td>      <td valign=top align=right><p align=right>2,749 </td>     </tr>     <tr>      <td valign=top> December </td>      <td valign=top align=right><p align=right>774,686 </td>      <td valign=top align=right><p align=right>2,335 </td>     </tr>     <tr>      <td valign=top> January </td>      <td valign=top align=right><p align=right>920,375 </td>      <td valign=top align=right><p align=right>2,812 </td>     </tr>     <tr>      <td valign=top> February </td>      <td valign=top align=right><p align=right>1,029,000 </td>      <td valign=top align=right><p align=right>2,883 </td>     </tr>     <tr>      <td valign=top> March </td>      <td valign=top align=right><p align=right>880,496 </td>      <td valign=top align=right><p align=right>2,234 </td>     </tr>     <tr>      <td valign=top> April </td>      <td valign=top align=right><p align=right>806,085 </td>      <td valign=top align=right><p align=right>2,358 </td>     </tr>     <tr>      <td valign=top> May </td>      <td valign=top align=right><p align=right>1,049,908 </td>      <td valign=top align=right><p align=right>2,856 </td>     </tr>     <tr>      <td valign=top> June </td>      <td valign=top align=right><p align=right>715,756 </td>      <td valign=top align=right><p align=right>882 </td>     </tr>     <tr>      <td valign=top> July </td>      <td valign=top align=right><p align=right><span class=underline>538,301</span> </td>      <td valign=top align=right><p align=right><span class=underline>662</span> </td>     </tr>     <tr>      <td valign=top> Total </td>      <td valign=top align=right><p align=right><span class=underline>$10,558,242</span> </td>      <td valign=top align=right><p align=right><span class=underline>25,561</span> </td>     </tr>     <tr>      <td valign=top> Average </td>      <td valign=top align=right><p align=right><span class=underline>$ 812,172</span> </td>      <td valign=top align=right><p align=right><span class=underline>1,966</span> </td>     </tr>    </tbody>   </table> The controller’s office has analyzed the data and given you the results from the regression analysis:   <span class=bold><span class=italics>Required</span></span> <span class=italics>a.</span> In the standard regression equation <span class=italics>y = a + bx,</span> the letter <span class=italics>b</span> is best described as the (1) Independent variable. (2) Dependent variable. (3) Constant coefficient. (4) Correlation coefficient. (5) Variable cost coefficient. <span class=italics>b.</span> In the standard regression equation <span class=italics>y = a + bx,</span> the letter <span class=italics>y</span> is best described as the (1) Independent variable. (2) Correlation coefficient. (3) Constant coefficient. (4) Variable cost coefficient. (5) Dependent variable. <span class=italics>c.</span> In the standard regression equation <span class=italics>y = a + bx,</span> the letter <span class=italics>x</span> is best described as the (1) Independent variable. (2) Dependent variable. (3) Constant coefficient. (4) Variable cost coefficient. (5) Correlation coefficient. <span class=italics>d.</span> If the controller uses the high-low method to estimate costs, the cost equation for administrative costs is (numbers are rounded to the nearest dollar) (1) Cost = $291,637 + 229 × Credit hours. (2) Cost = $233,571 + 101 × Credit hours. (3) Cost = $229.50 × Credit hours. (4) Cost = $404,874. (5) Some other equation. <span class=italics>e.</span> Based on the results of the controller’s regression analysis, the estimate of administrative costs in a month with 2,100 credit hours would be (1) $834,993. (2) $844,200. (3) $404,917. (4) $839,575. (5) Some other amount. <span class=italics>f.</span> The correlation coefficient (rounded) for the regression equation for administrative costs is (1) 0.871. (2) 0.933. (3) 0.859. (4)   (5) Some other amount. <span class=italics>g.</span> The percent of the total variance (rounded) that can be explained by the regression is (1) 85.9. (2) 87.1. (3) 93.3. (4) 96.6. (5) Some other amount.

(5) Some other amount.


g. The percent of the total variance (rounded) that can be explained by the regression is

(1) 85.9.

(2) 87.1.

(3) 93.3.

(4) 96.6.

(5) Some other amount.

Step-by-step solution
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a.

In the regression equation, the term b is not a constant value it changes. The value of b is not dependent on any other value. the value of b is neither a relation nor the Independent.


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Fundamentals of Cost Accounting 3rd Edition by William N. Lanen, Shannon W. Anderson, Michael Maher
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