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bixtya [17]
1 year ago
5

Ohio Swiss Milk Products manufactures and distributes ice cream in Ohio, Kentucky, and West Virginia. The company wants to expan

d operations by locating another plant in northern Ohio. The size of the new plant will be a function of the expected demand for ice cream within the area served by the plant. A mar-ket survey is currently under way to determine that demand. Ohio Swiss wants to estimate the relationship between the manufacturing cost per gallon and the number of gallons sold in a year to determine the demand for ice cream and, thus, the size of the new plant. The following data have been collected.
Plant Cost per Thousand Gallons (Y) Thousands of Gallons Sold (X)
1 $1,015 416.9
2 973 472.5
3 1,046 250
4 1,006 372.1
5 1,058 238.1
6 1,068 258,6
7 967 597
8 997 414
9 1,044 263.2
10 1,008 372
Total $10,182 3,654.40

Required:
a. Develop a regression equation to forecast the cost per gallon as a function of the number of gallons produced.
b. What are the correlation coefficient and the coefficient of determination? Comment on your regression equation in light of these measures.
c. Suppose that the market survey indicates a demand of 325,000 gallons in the Bucyrus Ohio, area. Estimate the manufacturing cost per gallon for a plant producing 325,000 gallons peryear.
Business
1 answer:
LenaWriter [7]1 year ago
3 0

Answer:

a. The regression equation required is Y = 915.18 – 0.2819X.

b. b-1. Correlation coefficient (r) = –0.9423

b-2. Coefficient of determination = r^2 = 88.80%

b-3. The negative correlation coefficient of -0.9423 implies that increase in X mostly causes a decrease in Y. The coefficient of determination implies that 88.80% variation in Y is explained by X.

c. The manufacturing cost per gallon is $823.56.

Explanation:

Note: See the attached excel file for the calculation of Mean of X and Y and other values.

a. Develop a regression equation to forecast the cost per gallon as a function of the number of gallons produced.

The regression can be written as follows:

Y = bo + b1X ………………… (1)

b1 = (Sum of (Y - Mean of Y) * (X - Mean of X)) / (Sum of (X - Mean of X)^2) = –34,273.08 / 121,585.14 = –0.2819

b0 = Mean of Y – (b1 * Mean of X) = 1,018.20 - (365.44 * 0.2819) = 915.18

Substituting b) and b1 values into equation (1), regression equation to forecast the cost per gallon as a function of the number of gallons produced can be written as follows:

Y = 915.18 – 0.2819X ……………………….. (2)

Equation (2) is the regression equation required.

b. What are the correlation coefficient and the coefficient of determination? Comment on your regression equation in light of these measures.

b-1. Correlation coefficient (r) can be calculated using the following formula:

r = (Sum of (Y - Mean of Y) * (X - Mean of X)) / ((Sum of (Y - Mean of Y)^2) * (Sum of (X - Mean of X)^2))^0.5 = –34,273.08 / (10,879.60 * 121,585.14)^0.5 = –0.9423

b-2. Coefficient of determination = r^2 = –0.94^2 = 0.8880, or 88.80%

b-3. The negative correlation coefficient of -0.9423 implies that increase in X mostly causes a decrease in Y. The coefficient of determination implies that 88.80% variation in Y is explained by X.

c. Suppose that the market survey indicates a demand of 325,000 gallons in the Bucyrus Ohio, area. Estimate the manufacturing cost per gallon for a plant producing 325,000 gallons per year.

Since X and Y are in thousands, 325,000 gallons implies we have:

X = 325

Substitute X = 325 into equation (2), we have:

Y = 915.18 - (0.2819 * 325)

Expressing in full form, we have:

Y = $823

Therefore, the manufacturing cost per gallon is $823.56.

Download xlsx
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Answer:

210

Explanation:

Let us consider that x is the number of soldiers produced each week and y is number of trains produced each week.

Also, weekly revenues and costs can be expressed in terms of the decision variables x and y.

Then,

Hence the profit which we want to maximize is given by,

Now the constraints are given as,

Finishing Constraint:

Each week, no more than 100 hours of finishing time may be used.

Carpentry Constraint:

Each week, no more than 80 hours of carpentry time may be used.

Demand Constraint:

Because of limited demand, at most 40 soldiers should be produced each week.

Combining the sign restrictions and with the objective function  and constraints,and yield the following optimization model:

Such that,

First convert the given inequalities into equalities:

From equation (1):

If x=0 in equation (1) then (0,100)

If y=0 in equation (1) then (50,0)

From equation (2):

If x=0 in equation (2) then (0,80)

If y=0 in equation (2) then (80,0)

From equation (3):

Equation (3) is the line passing through the point x=40.

Therefore, the given LPP has a feasible solution first image

The optimum solution for the given LPP is obtained as follows in the second image

The optimal solution to this problem is,

And the optimum values are  .

Let c be the contribution to profit by each train. We need to find the values of c for which the current, basis remain optimal. Currently c is 2, and each iso-profit line has the form

3x +  2y = constant

y = 3x/2 +constant/ 2

And so, each iso-profit line has a slope of  .

From the graph we can see that if a change in c causes the isoprofit lines to be flatter than the carpentry constraint, then the optimal solution will change from the current optimal solution to a new optimal solution, If the profit for each train is c, the slope of each isoprofit line will be.

-3/c

Because the slope of the carpentry constraint is –1, the isoprofit lines will be flatter than the carpentry constraint.

If,

-3/c<-1

c >3

and the current basis will no longer be optimal. The new optimal solution will be point A of the graph.

If the is oprofit lines are steeper than the finishing constraint, then the optimal solution will change from point B to point C. The slope of the finishing constraint is –2.

If,

-3/c < -2 or

C < 1.5

Then the current basis is no longer optimal and point C,(40,20), will be optimal. Hence when the contribution to the profit for trains is between $1.50 and $3, the current basis remains optimal.

Again, consider the contribution to the profit for trains is $2.50, then the decision variables remain the same since the contribution to the profit for trains is between $1.50 and $3. And the optimal solution is given by,

z = 3× (20) + 2.5 × (60)

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Bob,s candle factory is considering three different manufacturing options. Option A uses hand labor with fixed costs of $10,000
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Answer:

a. If demand for Bob's candles is 2500, which option should he pick?

  • OPTION A

and what is the cost?

  • $16,875

b. If demand for Bob's candles is 4500 which option should he $19,950

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and what is the cost?

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Explanation:

Option A uses hand labor with fixed costs of $10,000 and variable costs of $2.75/candle.

Option B uses a combination of hand and automation with fixed costs of $15,000 and variable costs of $1.10/candle.

Option C is highly automated with fixed costs of $20,000 and variable costs of $0.75/candle.

demand = 2,500 units

option A = $10,000 + ($2.75 x 2,500) = $16,875

option B = $15,000 + ($1.10 x 2,500) = $17,750

option C = $20,000 + ($0.75 x 2,500) = $21,875

demand = 4,500 units

option A = $10,000 + ($2.75 x 4,500) = $22,375

option B = $15,000 + ($1.10 x 4,500) = $19,950

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Complete question:

Bressler’s would like to sell 600shares of stock using the Dutch auction method. The bids received are as follows:

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    B                 300            17

    C                400             16

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