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Thane Company Is Interested in Establishing the Relationship Between Electricity

question 22

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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:
MonthMachine HoursElectricity Costs January 2,500$18,400 February 2,90021,000 March 1,90013,500 April 3,10023,000 May 3,80028,250 June 3,30022,000 July 4,10024,750 August 3,50022,750 September 2,00015,500 October 3,70026,000 November 4,70031,000 December 4,20027,750\begin{array}{lll}\text {Month}&\text {Machine Hours}&\text {Electricity Costs}\\\text { January } & 2,500 & \$ 18,400 \\\text { February } & 2,900 & 21,000 \\\text { March } & 1,900& 13,500 \\\text { April } & 3,100 & 23,000 \\\text { May } & 3,800& 28,250 \\\text { June } & 3,300& 22,000 \\\text { July } & 4,100 & 24,750\\\text { August } & 3,500 & 22,750 \\\text { September } & 2,000 & 15,500 \\\text { October } & 3,700 & 26,000 \\\text { November } & 4,700 & 31,000 \\\text { December } & 4,200 & 27,750\end{array}



 Summary Output  Regression Statistics  Multiple R 0.965 R Squuare 0.932 Adjusted R 20.925 Standard Error 1,425.18 Observations 12.00\begin{array}{c} { \text { Summary Output } } \\ { \text { Regression Statistics } } \\\begin{array}{ | l | c | } \hline \text { Multiple R } & 0.965 \\\hline \text { R Squuare } & 0.932 \\\hline \text { Adjusted R } ^2 & 0.925 \\\hline \text { Standard Error } & 1,425.18 \\\hline \text { Observations } & 12.00 \\\hline\end{array}\end{array}
 Standard  Lower  Upper  Coefficients  Error  t Stat  P-value 95%95% Intercept 3,726.881,682.822.210.05(22.69) 7,476.45 Machine 5.770.4911.70.004.676.87 Hours \begin{array}{|l|r|r|r|r|r|r|}\hline && \text { Standard } & && \text { Lower } & \text { Upper } \\&\text { Coefficients } & \text { Error } & \text { t Stat } & \text { P-value } & 95 \% & 95 \% \\ \hline \text { Intercept } & 3,726.88 & 1,682.82 & 2.21 & 0.05 & (22.69) & 7,476.45 \\\hline \text { Machine } & 5.77 & 0.49 & 11.7 & 0.00 & 4.67 & 6.87 \\\text { Hours } & & & & & \\\hline\end{array}



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


Definitions:

Flexible Budget Amounts

Budgeted figures that can adjust based on changes in activity levels or other factors, unlike a static budget.

Variable Costs

Expenses that change in proportion to the volume of production or sales, including components like raw materials and direct labor costs.

Fixed Costs

Expenses that do not change with the level of goods or services produced within a certain time span.

Operating Income

The profit realized from a business's core operations, excluding deductions of interest and taxes.

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