Burmer Co. has accumulated data to use in preparing its annual profit plan for the upcoming year. The cost behavior pattern of the maintenance costs must be determined. Data regarding the machine hours and maintenance costs for the last year and the results of the regression analysis are as follows: Month Maintenance Cost Machine Hours Jan. $5,040 620 Feb. 3,600 420 Mar. 4,320 520 Apr. 3,380 390 May 5,220 650 June 3,550 400 July 3,640 430 Aug. 5,360 680 Sept. 5,110 640 Oct. 4,860 610 Nov. 3,960 460 Dec. 3,790 440 Sum $51,830 6,260 Average $4,319 522 A staff assistant has run regression analyses on the data and obtained the following output using Excel: REGRESSION ANALYSIS Y (Dependent) Variable: Maintenance Cost X (Independent) Variable: Maintenance Hours Regression Statistics Multiple R 0.998210294 R Square 0.996423791 Adjusted R Square 0.99606617 Standard Error 47.0629563 Observations 12 ANOVA df SS MS F Significance F Regression 1 6171342.448 6171342 2786.257 1.44166E-13 Residual 10 22149.21856 2214.922 Total 11 6193491.667 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 783.7782188 68.34114772 11.46861 4.47E-07 631.504653 936.051785 Hours 6.777102456 0.12839066 52.78501 1.44E-13 6.491030239 7.06317467 The 95% confidence range for a prediction of monthly manufacturing cost using the model is: