You are considering constructing a new plant in a remote wilderness area to process the ore from a planned mining operation. You anticipate that the plant will take a year to build and cost $120 million upfront. Starting in t=1, it will generate cash flows of $19 million at the end of every year over the life of the plant. The plant will be useless 20 years later, once the mine runs out of ore. In t=21 you expect to pay another $120 million to shut the plant down and restore the area to its pristine state. Using a cost of capital of 8,9%, a. What is the NPV of the project? b. Is using the IRR rule reliable for this project? Explain in 1-2 sentences.
In: Finance
You are considering constructing a new plant in a remote wilderness area to process the ore from a planned mining operation. You anticipate that the plant will take a year to build and cost $ 96 million upfront. Once built, it will generate cash flows of $ 16 million at the end of every year over the life of the plant. The plant will be useless 20 years after its completion once the mine runs out of ore. At that point you expect to pay $ 224 million to shut the plant down and restore the area to its pristine state. Using a cost of capital of 11 %: a. What is the NPV of the project? b. Is using the IRR rule reliable for this project? Explain. c. What are the IRRs of this project?
In: Finance
a. What is the optional run size and lowest annual cost for carrying and setup?
b. What are the cycle time and run time for the optimal run quantity?
c. If the company wants to run another production for a new product between runs of this item, and needs a minimum of 10 days per cycle for the other work, will there be enough time?
In: Operations Management
Write a program that uses a structure to store the following weather data for a particular month: Total Rainfall High Temperature Low Temperature Average Temperature.
The program should have an array of 12 structures to hold weather data for an entire year.
When the program runs, it should ask the user to enter data for each month. (The average temperature should be calculated.)
Once the data are entered for all the months, the program should calculate and display the average monthly rainfall, the total rainfall for the year, the highest and lowest temperatures for the year (and the months they occurred in), and the average of all the monthly average temperatures. Input Validation: Only accept temperatures within the range between –100 and +140 degrees Fahrenheit.
In: Computer Science
9. A 60 kg football receiver starts from rest, accelerating at a rate of 0.36 g’s for 1.42 seconds until he runs as fast as he can. A ball of mass 0.25 kg is thrown, and the player catches the ball 3.35 seconds after the play starts. If the ball is travelling at 16 m/s when the player catches it, (a) how far down field did the player catch it, (b) what will the player’s final speed be after catching the ball, (c) what are the kinetic energies of the ball and player separately before the catch, and (d) what is the kinetic energy of the ball – player system after the catch? (e) Compare your results of (c) and (d) and explain.
In: Physics
JAVA PROGRAM, Create the game "Rock, Scissor, Paper":
In: Computer Science
PYTHON WHILE Write a program that prompts for and reads the number ? of spheres to be processed. If ?≤0 your program must display an error message and terminate; otherwise it does the following for ? times:
In: Computer Science

The number of heart surgeries performed at Heartville General Hospital has increased steadily over the past several years. The hospital's administration is seeking the best method to forecast the demand for such surgeries in year 6. The data for the past five years are shown below.
| Year | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
| Demand | 44 | 47 | 54 | 57 | 61 |
The hospital's administration is considering the following forecasting methods. Begin error measurement in year 3, so all methods are compared for the same years
i. Exponential smoothing, with a 0.6. Let the initial forecast for year 1 be 44, the same as the actual demand.
ii, Exponential smoothing, with o: 0.9 Let the initial forecast for year 1 be 44, the same as the actual demand.
iii. Trend projection with regression
iv. Two-year moving average.
v. Two-year weighted moving average, using weights 0.6 and 0.4, with the more recent data given more weight.
If MAD is the performance criterion chosen by the administration, which forecasting method should it choose? Trend projection with regression
If MSE is the performance criterion chosen by the administration, which forecasting method should it choose?
In: Other
| Sales price, y (thousands) | Square feet, x1 | Rooms, x2 | Bedrooms, x3 | Age, x4 |
| 53.5 | 1008 | 5 | 2 | 35 |
| 49 | 1290 | 6 | 3 | 36 |
| 50.5 | 860 | 8 | 2 | 36 |
| 49.9 | 912 | 5 | 3 | 41 |
| 52 | 1204 | 6 | 3 | 40 |
| 55 | 1204 | 5 | 3 | 10 |
| 80.5 | 1764 | 8 | 4 | 64 |
| 86 | 1600 | 7 | 3 | 19 |
| 69 | 1255 | 5 | 3 | 16 |
| 149 | 3600 | 10 | 5 | 17 |
| 46 | 864 | 5 | 3 | 37 |
| 38 | 720 | 4 | 2 | 41 |
| 49.5 | 1008 | 6 | 3 | 35 |
| 103 | 1950 | 8 | 3 | 52 |
| 152.5 | 2086 | 7 | 3 | 12 |
| 85 | 2011 | 9 | 4 | 76 |
| 60 | 1465 | 6 | 3 | 102 |
| 58.5 | 1232 | 5 | 2 | 69 |
| 101 | 1736 | 7 | 3 | 67 |
| 79.4 | 1296 | 6 | 3 | 11 |
| 125 | 1996 | 7 | 3 | 9 |
| 87.9 | 1874 | 5 | 2 | 14 |
| 80 | 1580 | 5 | 3 | 11 |
| 94 | 1920 | 5 | 3 | 14 |
| 74 | 1430 | 9 | 3 | 16 |
| 69 | 1486 | 6 | 3 | 27 |
| 63 | 1008 | 5 | 2 | 35 |
| 67.5 | 1282 | 5 | 3 | 20 |
| 35 | 1134 | 5 | 2 | 74 |
| 142.5 | 2400 | 9 | 4 | 15 |
| 92.2 | 1701 | 5 | 3 | 15 |
| 56 | 1020 | 6 | 3 | 16 |
| 63 | 1053 | 5 | 2 | 24 |
| 60 | 1728 | 6 | 3 | 26 |
| 34 | 416 | 3 | 1 | 42 |
| 52 | 1040 | 5 | 2 | 9 |
| 75 | 1496 | 6 | 3 | 30 |
| 93 | 1936 | 8 | 4 | 39 |
| 60 | 1904 | 7 | 4 | 32 |
| 73 | 1080 | 5 | 2 | 24 |
| 71 | 1768 | 8 | 4 | 74 |
| 83 | 1503 | 6 | 3 | 14 |
| 90 | 1736 | 7 | 3 | 16 |
| 83 | 1695 | 6 | 3 | 12 |
| 115 | 2186 | 8 | 4 | 12 |
| 50 | 888 | 5 | 2 | 34 |
| 55.2 | 1120 | 6 | 3 | 29 |
| 61 | 1400 | 5 | 3 | 33 |
| 147 | 2165 | 7 | 3 | 2 |
| 210 | 2353 | 8 | 4 | 15 |
| 60 | 1536 | 6 | 3 | 36 |
| 100 | 1972 | 8 | 3 | 37 |
| 44.5 | 1120 | 5 | 3 | 27 |
| 55 | 1664 | 7 | 3 | 79 |
| 53.4 | 925 | 5 | 3 | 20 |
| 65 | 1288 | 5 | 3 | 2 |
| 73 | 1400 | 5 | 3 | 2 |
| 40 | 1376 | 6 | 3 | 103 |
| 141 | 2038 | 12 | 4 | 62 |
| 68 | 1572 | 6 | 3 | 29 |
| 139 | 1545 | 6 | 3 | 9 |
| 140 | 1993 | 6 | 3 | 4 |
| 55 | 1130 | 5 | 2 | 21 |
The excel data file named “Family-Residences Data” (posted in the content area under Week IX) presents the sale price y (thousands), square footage (x1), number of rooms (x2), number of bedrooms (x3), and age (x4) for each of 63 single-family residences sold in Oxford, Ohio. Use any software of your choice to conduct a multiple regression analysis for this data set. Use the result of this analysis to answer the questions below.
1. Write a regression model that relates the dependent variable
to the independent variables.
2. Interpret the error term in this model. What does it represent?
3. Identify the least squares point estimates of
b0, b1, b2, b3, and
b4 from your software output. Approximate these to
four decimal places when necessary.
4. Write a multiple regression equation that relates sale price
to square footage, number of rooms, number of bedrooms, and
age.
5. Does the model explain a substantial portion of the
variability in sale prices? Explain.
6. Do the signs and magnitudes of the estimated coefficients
appear to be reasonable? Explain.
7. Write the multiple regression hypotheses to be tested.
8. Use F test to test the adequacy of the model with a = .05.
Interpret the result of this test.
9. Use the p-value from your software output to test the
importance of each of the independent variables x1,
x2, x3, and x4 at a= .05. Which
variables are not important? Explain.
10. Use the residential sales estimated equation to predict sales price of a residence that has 1700 square feet, seven rooms, and three bedrooms and is 15 years old.
In: Statistics and Probability
Suppose there are two beer companies. One produces a beer that has a high alcohol content (ABV 10%), while the other company produces a light beer that has a low ABV (5%). Assume there are 50 consumers whose preferences for alcohol content (ABV) are uniformly distributed between 5% and 10%. Consumers all value drinking a beer their ideal beer at $10 but dislike a beer with a different ABV than their ideal ABV by $1 per percentage point. That is, if I prefer a beer with 6% ABV and I drink the light beer, my utility will be $1 lower. If I prefer a beer with 5.5% and I drink the light beer my utility will be $0.50 lower. Marginal cost is the same for both companies and is equal to $1. The two companies compete by choosing prices simultaneously.
1. What is the utility of purchasing the low ABV beer for a consumer whose preferred beer contains x ABV?
2. What is the utility of purchasing the high ABV beer for a consumer whose preferred beer contains x ABV?
3. Find an expression for the “location” of marginal consumer given pl and ph. In other words, given prices, what is the ABV preference for a consumer who is indifferent between consuming the light beer and the heavy beer. Call this function x m(pl , ph).
4. What happens to the “location” of the marginal consumer as the price of the heavy beer increases?
5. Using this expression, what is the demand curve for the two beers?
6. What is the profit function for each firm?
7. What is the best response function of each firm?
8. Solve for the pure strategy Nash Equilibrium in prices. What are profits in this equilibrium?
In: Economics