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The College of Business at Northeast College Is Accumulating Data

Question 70

Multiple Choice

The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:
 Administrative  Credit  Month  Costs  Hours  July $129,301250 August 82,613115 September 225,5801,392 October 216,3941,000 November 258,2631,309 December 184,4451,112 January 219,1371,335 February 245,0001,373 March 209,4621,064 April 191,9251,123 May 249,9781,360 June 170,41ε420 July 128,167315 Total $2,510,68712,172 Average $193,130936\begin{array}{lrr}& \text { Administrative } & \text { Credit } \\\text { Month } & \text { Costs } & \text { Hours }\\\text { July } & \$ 129,301 & 250 \\\text { August } & 82,613 & 115 \\\text { September } & 225,580 & 1,392 \\\text { October } & 216,394 & 1,000 \\\text { November } & 258,263 & 1,309\\\text { December } & 184,445 & 1,112 \\\text { January } & 219,137 & 1,335 \\\text { February } & 245,000 & 1,373 \\\text { March } & 209,462 & 1,064 \\\text { April } & 191,925 & 1,123 \\\text { May } & 249,978 & 1,360\\\text { June } & 170,41 \varepsilon & 420 \\\text { July } & 128,167 & 315 \\\text { Total } & \$ 2,510,687 & 12,172 \\\text { Average } & \$ 193,130 & 936\end{array}


The controller's office has analyzed the data and has given you the results from the regression analysis:
 SUMMARY OUTPUT  Regression Statistics  Multiple R 0.9317157 R Square 0.868094147 Adjusted R Square 0.856102705 Standard Error 20,134.92395 Observations 13\begin{array}{c} { \text { SUMMARY OUTPUT } } \\ { \text { Regression Statistics } } \\\begin{array} { | l | r | } \hline \text { Multiple R } & 0.9317157 \\\hline \text { R Square } & 0.868094147 \\\hline \text { Adjusted R Square } & 0.856102705 \\\hline \text { Standard Error } & 20,134.92395 \\\hline \text { Observations } & 13 \\\hline\end{array}\end{array}
 ANOVA  df S S  M S  F  Significance  F  Repression 129,349,143,51429,349,143,51472.39281173.61909E06 Residual 114,459,566,787405,415,162.4 Total 1233,808,710,301\begin{array} { | l | r | r | r | r | r | } \hline \text { ANOVA } & & & & & \\\hline & \text { df} & \text { S S } & \text { M S } & \text { F } & \text { Significance } \text { F } \\\hline \text { Repression } & 1 & 29,349,143,514 & 29,349,143,514 & 72.3928117 & 3.61909 \mathrm { E } - 06 \\\hline \text { Residual } & 11 & 4,459,566,787 & 405,415,162.4 & & \\\hline \text { Total } & 12 & 33,808,710,301 & & & \\\hline\end{array}

 The College of Business at Northeast College is accumulating data as a first step in the preparation of next year's budget development. One cost that is being looked at closely is administrative costs as a function of student credit hours. Data on administrative costs and credit hours for the past thirteen months are shown below:  \begin{array}{lrr} & \text { Administrative } & \text { Credit } \\ \text { Month } & \text { Costs } & \text { Hours }\\ \text { July } & \$ 129,301 & 250 \\ \text { August } & 82,613 & 115 \\ \text { September } & 225,580 & 1,392 \\ \text { October } & 216,394 & 1,000 \\ \text { November } & 258,263 & 1,309\\ \text { December } & 184,445 & 1,112 \\ \text { January } & 219,137 & 1,335 \\ \text { February } & 245,000 & 1,373 \\ \text { March } & 209,462 & 1,064 \\ \text { April } & 191,925 & 1,123 \\ \text { May } & 249,978 & 1,360\\ \text { June } & 170,41 \varepsilon & 420 \\ \text { July } & 128,167 & 315 \\ \text { Total } & \$ 2,510,687 & 12,172 \\ \text { Average } & \$ 193,130 & 936 \end{array}    The controller's office has analyzed the data and has given you the results from the regression analysis:  \begin{array}{c}    { \text { SUMMARY OUTPUT } } \\  { \text { Regression Statistics } } \\ \begin{array} { | l | r | }  \hline \text { Multiple R } & 0.9317157 \\ \hline \text { R Square } & 0.868094147 \\ \hline \text { Adjusted R Square } & 0.856102705 \\ \hline \text { Standard Error } & 20,134.92395 \\ \hline \text { Observations } & 13 \\ \hline \end{array}\end{array}   \begin{array} { | l | r | r | r | r | r | }  \hline \text { ANOVA } & & & & & \\ \hline & \text { df} &  \text { S S } &  \text {  M S } &  \text {  F } & \text { Significance }  \text {  F } \\ \hline \text { Repression } & 1 & 29,349,143,514 & 29,349,143,514 & 72.3928117 & 3.61909 \mathrm { E } - 06 \\ \hline \text { Residual } & 11 & 4,459,566,787 & 405,415,162.4 & & \\ \hline \text { Total } & 12 & 33,808,710,301 & & & \\ \hline \end{array}     - Based on the results of the regression analysis, the estimate of administrative costs in a month with 1,000 credit hours would be: (rounded to the nearest whole dollar)  A)  $198,808. B)  $201,000. C)  $199,707. D)  $96,409.
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Based on the results of the regression analysis, the estimate of administrative costs in a month with 1,000 credit hours would be: (rounded to the nearest whole dollar)


A) $198,808.
B) $201,000.
C) $199,707.
D) $96,409.

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