The Armer Company is accumulating data to be use in preparing its annual profit plan for the coming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff has suggested the use of linear regression to derive an equation for maintenance hours and costs. Data regarding the maintenance hours and costs for the last year and the results of the regression analysis follow: Month Maintenance Cost Machine Hours Jan. $ 4,200 480 Feb. 3,000 320 Mar. 3,600 400 Apr. 2,820 300 May 4,350 500 June 2,960 310 July 3,030 320 Aug. 4,470 520 Sept. 4,260 490 Oct. 4,050 470 Nov. 3,300 350 Dec. 3,160 340 Sum $ 43,200 4,800 Average $ 3,600 $ 400 Average cost per hour $ 9.00 a (intercept) $ 684.65 b (coefficient) 7.2884 Standard error of the estimate 34.469 R-squared 0.99724 t-value for b 60.105 Based on the data derived from the regression analysis, 420 maintenance hours in a month mean that maintenance costs should be budgeted to the nearest dollar at:.

Based on the data derived from the regression analysis, 420 maintenance hours in a month mean that maintenance costs should be budgeted to the nearest dollar at: $3,746.

Explanation:

From the regression results given in the question, we can obtain the following:

a. Intercept = $684.65

b. Coefficient = $7.2884

Based on the above, the estimated regression equation can be provided as follows:

Maintenance costs = $684.65 + ($7.2884 * Maintenance hours) (1)

Since we are given 420 maintenance hours in a month, we therefore substitute "Maintenance hours = 420" into equation (1) to obtain the maintenance costs that should be budgeted as follows:

Maintenance costs = $684.65 + ($7.2884 * 420) = $684.65 + $3,061.128 = $3,745.778

Rounding to the nearest dollars, we have:

Maintenance costs = $3,746

Therefore, based on the data derived from the regression analysis, 420 maintenance hours in a month mean that maintenance costs should be budgeted to the nearest dollar at: $3,746.

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