The Armer Company is accumulating data to be used 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 that linear regression be employed to derive an equation in the form of y = a + bx for maintenance costs. Data regarding the maintenance hours and costs for last year and the results of the regression analysis are as follows:

	Hours of Activity		Maintenance Costs
January	440		$ 3,900
February	320		2,500
March	370		3,000
April	350		2,900
May	550		4,330
June	330		2,710
July	340		3,520
August	470		4,770
September	520		4,230
October	520		4,460
November	380		3,200
December	380		3,550
Sum	4,970		43,070
Average	414		3,589

A coefficient			246.88
B coefficient			8.0699
Standard error of the a cofficient	556.244
Standard error of the a cofficient	1.31938
Standard error of the estimate			360.101
R2			0.78908
T-value a			.444
T-value b			6.116

Based upon the data derived from the regression analysis, 420 maintenance hours in a month would mean the maintenance costs would be budgeted at: (rounded to the nearest whole dollar)