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Using Both High-Low and Regression

John Meeks Company is a medium-size manufacturing company with plants in three small mid-Atlantic towns. The company makes plastic parts for automobiles and trucks, primarily door panels, exterior trim, and related items. The parts have an average cost of $5 to $20. The company has a steady demand for its products from both domestic and foreign automakers and has experienced growth in sales averaging between 10 and 20 percent over the last 8 to 10 years.

Currently, management is reviewing the incidence of scrap and waste in the manufacturing process at one of its plants. Meeks defines scrap and waste as any defective unit that is rejected for lack of functionality or another aspect of quality. The plants have a number of different inspection points, and failure or rejection can occur at any inspection point. The number of defective units is listed in the following table; management estimates the cost of this waste in labor and materials is approximately $10 per unit.

An unfavorable trend appears to exist with regard to defects, and management has asked you to investi- gate and estimate the defective units in the coming months. A first step in your investigation is to identify the cost drivers of defective parts, to understand what causes them, and to provide a basis on which to esti- mate future defects. For this purpose, you have obtained these recent data on the units produced, the units shipped, and the cost of sales since these numbers are easily available and relatively reliable on a monthly basis:


Units Produced(000s)

Cost of Sales(000s)

Units Shipped(000s)

DefectiveUnits

Jan 2009

55

$ 689

50

856

Feb

58

737

53

1,335

Mar

69

886

64

1,610

Apr

61

768

56

1,405

May

65

828

60

1,511

Jun

69

878

64

1,600

Jul

75

962

70

1,570

Aug

81

1,052

76

1,910

Sep

70

1,104

80

2,011

Oct

79

1,224

89

2,230

Nov

82

1,261

92

2,300

Dec

70

1,020

74

1,849

Jan 2010

67

850

62

1,549

Feb

72

916

67

1,669

Mar

85

1,107

80

2,012

Apr

75

968

70

1,756

May

81

1,037

76

1,889

Jun

85

1,103

80

1,650

Jul

92

1,208

87

2,187

Aug

100

1,310

95

2,387

Sep

91

1,380

101

2,514

Oct

101

1,536

111

2,787

Nov

105

1,580

115

2,310

Dec

88

1,270

92

2,311

Required Use the high-low method and regression analysis to estimate the defective units in the coming months and to determine which method provides the best fit for this purpose.

Accounting Basics, Accounting

  • Category:- Accounting Basics
  • Reference No.:- M91886546

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