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Assignment of Quantative Applications in Management

Autor:   •  April 16, 2015  •  Course Note  •  1,022 Words (5 Pages)  •  964 Views

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Assignment

Of

Quantative Applications in Management

Question 1.

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[pic 2]

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Standard deviation of x (σx) = [Σ(x - a)2 / N ]1/2

                               = [93750 / 6 ]1/2

                               = [15625]1/2

                               = 125

Standard deviation of x (σy) = [Σ(y - b)2 / N ]1/2

                               = [5648336 / 6 ]1/2

                               = [941389.333]1/2

                               = 970.25

a) Regression Equation

        y = 1246 + 7.6 x


b) Variable cost per unit = ______Total Cost________

                            Total no. of units produced

                        =  33700

                             3450

                        =  9.76

c) Coefficient of Determination

        R2 = { 1/N [Σ(x - a)(y - b)] / [σx σy] }2

             =  { 1/6 [712500] / [σx σy] }2

             =  { 1/6 [712500] / [(125)(970.25)] }2

             =  { 1/6 [5.87477] }2

             =  { 1/6 [5.87477] }2

             =  {0.9791}2

             =  0.9586

d) Estimated total cost for operation at 500 units of production

        y = 1246 + 7.6 x

where x = 500

        y = 1246 + 7.6 (500)

           = 1246 + 3800

           = 5046


Question 2.

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[pic 5]

Late Arri

Late Dep

x - a

y - b

(x - a)(y - b)

(x - a)2

(y - b)2

x

y

24

22

3

1.6

4.8

9

2.56

20

20

-1

-0.4

0.4

1

0.16

30

29

9

8.6

77.4

81

73.96

20

19

-1

-1.4

1.4

1

1.96

20

22

-1

1.6

-1.6

1

2.56

23

23

2

2.6

5.2

4

6.76

18

19

-3

-1.4

4.2

9

1.96

20

16

-1

-4.4

4.4

1

19.36

18

18

-3

-2.4

7.2

9

5.76

21

22

0

1.6

0

0

2.56

25

22

4

1.6

6.4

16

2.56

18

17

-3

-3.4

10.2

9

11.56

16

16

-5

-4.4

22

25

19.36

Σx = 273

Σy = 265

Σ(x - a)(y - b) = 142

Σ(x - a)2 = 166

Σ(y - b)2 = 151.08

Mean (a) = 21

Mean (b) = 20.38

b1 = Σ(x - a)(y - b) / Σ(x - a)2

b0 = b - b1a

b1 = 142 / 166

b0 = 20.38 - (0.855)(21)

b1 = 0.855

b0 = 20.38 - 17.955 = 2.42

c) Regression Equation

...

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