56) The total fixed cost is

A) \$39,250.

B) \$17,816.

C) \$2,200.

D) \$536.

57) The cost function would be stated as

A) Y = \$ 2,200 + \$2.80X.

B) Y = \$17,816 + \$0.36X.

C) Y = \$   536 + \$3.06X.

D) Y = \$39,250 + \$0.33X.

58) The total cost at an operating level of 10,000 units would be

A) \$31,136.

B) \$30,200.

C) \$21,416.

D) \$42,550.

The Vern Corporation has assembled the following data pertaining to certain costs that cannot be easily identified as either fixed or variable.  Vern Corporation has heard about a method of measuring cost functions called the high-low method and has decided to use it in this situation.

 Cost Hours \$20,000 7,000 12,200 4,000 17,000 5,200 15,640 4,900 18,200 6,000 22,080 7,800 21,200 7,480 18,600 6,760

59) The variable cost per unit is

A) \$0.38.

B) \$0.46.

C) \$2.60.

D) \$2.16.

60) The total fixed cost is

A) \$13,386.

B) \$10,680.

C) \$5,056.

D) \$1,800.

61) The cost function would be stated as

A) Y = \$13,386 + \$0.46X.

B) Y = \$10,680 + \$0.38X.

C) Y = \$ 5,056 + \$2.16X.

D) Y = \$ 1,800 + \$2.60X.

The Stewart Company used regression analysis to predict the annual cost of utilities.  The results were as follows:

Utilities Cost

Explained by Machine Hours

 Constant \$16,650 Standard error of Y estimate \$  3,726 R-squared 0.9436 No. of observations 24 Degrees of freedom 22 X coefficient(s) 7.16 Standard error of coefficient(s) 0.458329

62) The total fixed cost is

A) \$16,650.

B) \$15,711.

C) \$ 6,652.

D) \$ 3,726.

63) The variable cost per machine hour is

A) \$1.86.

B) \$0.96.

C) \$7.16.

D) \$0.46.

64) The linear cost function is

A) Y = \$16,650 + \$7.16X.

B) Y = \$15,711 + \$1.86X.

C) Y = \$ 3,726 + \$0.96X.

D) Y = \$ 6,562 + \$0.46X.

65) The coefficient of determination is

A) 0.458329.

B) 22.

C) 7.16.

D) 0.9436.