In preparing the annual profit plan for the coming year, Paul Company wants to determine the cost behavior pattern of the maintenance costs. Paul has decided to use linear regression by employing the equation y = a + bx for maintenance costs. The prior year's data regarding maintenance hours and costs are as follows. Hours of Maintenance Activity Costs January 480 P42,000 February 320 30,000 March 400 36,000 Аpril 300 58,200 May 500 43,500 June 310 29,600 July 320 30,300 August 520 44,700 September 490 42,600 October 470 40,500 November 350 33,000 December 340 31,600 4.800 P 462 000

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QUESTIONS ARE:
1.Using linear regression analysis, the estimated variable cost per labor hour for maintenance is closest to
2.Refer to Paul Company. Using linear regression analysis, the estimated fixed cost per month for maintenance is closest to
3.Refer to Paul Company. Based upon the data derived from the regression analysis, 450 maintenance hours
in a month would mean the maintenance costs
(rounded to the nearest peso) would be budgeted at

In preparing the annual profit plan for the coming year, Paul Company wants to determine the cost behavior
pattern of the maintenance costs. Paul has decided to use linear regression by employing the equation y = a
+ bx for maintenance costs. The prior year's data regarding maintenance hours and costs are as follows.
Hours of
Maintenance
Activity
Costs
January
480
P42,000
February
320
30,000
March
400
36,000
April
300
58,200
May
500
43,500
June
310
29,600
July
320
30,300
August
520
44,700
September
490
42,600
October
470
40,500
November
350
33,000
December
340
31,600
4,800
P 462,000
Transcribed Image Text:In preparing the annual profit plan for the coming year, Paul Company wants to determine the cost behavior pattern of the maintenance costs. Paul has decided to use linear regression by employing the equation y = a + bx for maintenance costs. The prior year's data regarding maintenance hours and costs are as follows. Hours of Maintenance Activity Costs January 480 P42,000 February 320 30,000 March 400 36,000 April 300 58,200 May 500 43,500 June 310 29,600 July 320 30,300 August 520 44,700 September 490 42,600 October 470 40,500 November 350 33,000 December 340 31,600 4,800 P 462,000
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