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

A key statistic that indicates reliability of the regression is:

Multiple Choice

• 12.

• 47.0630.

• 0.9964.

• 783.338.

• 6.777.