Senior executives at an oil company are trying to decide whether to drill for oil in a particular field. It costs the company $750,000 to drill. The company estimates that if oil is found the estimated value will be $3,650,000. At present, the company believes that there is a 48% chance that the field actually contains oil.  Develop a decision tree. the EMV is 1,002,000. Before drilling, the company can hire an expert at a cost of $75,000 to perform tests to make a prediction of whether oil is present. Based on a similar test, the probability that the test will predict oil on the field is 0.55. The probability of actually finding oil when oil was predicted is 0.85. The probability of actually finding oil when no oil was predicted is 0.2. What is the EMV if the company hires the expert?

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The following are sales revenues for a large utility company for years 1 through 11. Forecast revenue for years 12 through 15. Because we are forecasting four years into the future, you will need to use linear regression as your forecasting method. Note: Enter your answers in millions. YEAR 1 2345 5 6 7 8 9 10 11 Period 12 13 14 15 REVENUE (MILLIONS) $4,865.7 5,072.3 5,507.7 5,738.2 5,495.4 5,198.7 5,087.0 5,111.5 5,559.7 5,740.4 5,868.4 Forecast

GENERATE THE DECISION VARIABLE SOLUTION AND GENERATE A SENSITIVITY REPORT CASE 1. Julia's Food Booth Julia Robertson is a senior at Tech, and she's investigating different ways to finance her final year at school. She is considering leasing a food booth outside the Tech stadium at home football games. Tech sells out every home game, and Julia knows, from attending the games herself, that everyone eats a lot of food. She has to pay $1,000 per game for a booth, and the booths are not very large. Vendors can sell either food or drinks on Tech property, but not both. Only the Tech athletic department concession stands can sell both inside the stadium. She thinks slices of cheese pizza, hot dogs, and barbecue sandwiches are the most popular food items among fans and so these are the items she would sell. Most food items are sold during the hour before the game starts and during half time; thus it will not be possible for Julia to prepare the food while she is selling it. She must prepare…

Please help with correct answers: step by step: last time submitted- answers were incorrect A statistical program is recommended. The quarterly sales data (number of copies sold) for a college textbook over the past three years follow. Quarter Year 1 Year 2 Year 3 1 1,690 1,800 1,850 2 940 900 1,100 3 2,625 2,900 2,930 4 2,500 2,360 2,615 a) Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. (Round your numerical values to the nearest integer.) Qrt1 = 1 if quarter 1, 0 otherwise; Qrt2 = 1 if quarter 2, 0 otherwise; Qrt3 = 1 if quarter 3, 0 otherwise t =    b) Using the equation developed in part (b), compute the quarterly forecasts for year 4. (Round your answers to the nearest ten.) quarter 1 forecast____? quarter 2 forecast____? quarter 3 forecast ____? quarter 4 forecast ____?   c) Let t = 1 refer to the observation in Quarter 1 of Year 1; let  t = 2 refer to the observation in Quarter 2 of Year…

Miles Filtration, Inc. provides maintenance services for water filtration systems throughout Southern Florida. Customers contact Johnson with requests for maintenance service on their water filtration systems. To estimate service time and the service cost, Johnson’s managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors: the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performs the repair (Donna Newton or Bob Jones). Data for a sample of 10 service calls are reported in the following table: Develop the multiple regression equation to predict repair time, given the number of months since the last maintenance service, the repairperson, and the type of repair. What are the interpretations of the estimated regression parameters? What does the coefficient of…

At Tech Innovators Corporation, a study was conducted to assess employees' job satisfaction and their engagement in professional development activities. Out of the 500 employees surveyed: 220 employees reported being satisfied with their jobs. 350 employees were engaged in some form of professional development. 180 employees were both satisfied with their jobs and engaged in professional development. What is the probability that a randomly selected employee from the company is satisfied with their job? Given that an employee is engaged in professional development, what is the probability that they are also satisfied with their job? What is the probability that an employee who is not engaged in professional development is satisfied with their job?

The manager of a utility company in the Texas panhandle wants to develop quarterly forecasts of power loads for the next year. The power loads are seasonal, and the data on the quarterly loads in megawatts (MW) for the last four years are as follows: Year 3 117.6 Quarter Year 1 101.6 Year 4 101.5 Year 2 94.2 112.7 143.3 2 127.3 146.6 143.4 167.7 182.4 132.9 3 159.3 168.5 153.7 169.0 The manager estimates the total demand for the next year at 689 MW. Use the multiplicative seasonal method to develop the forecast for each quarter. (Round all intermediate calculations to three decimal places.) The first quarter forecast is MW. (Enter your response rounded to one decimal place.)

The University of Miami bookstore stocks textbooks in preparation for sales each semester. It normally relies on departmental forecasts and preregistration records to determine how many copies of a text are needed. Preregistration shows 85 operations management students enrolled, but bookstore manager Vaidy Jayaraman has second thoughts, based on his intuition and some historical evidence. Vaidy believes that the distribution of sales may range from 65 to 85 units, according to the following probability model: Demand Probability 65 0.05 Stock 65 70 75 80 85 70 0.25 This textbook costs the bookstore $82 and sells for $107. Any unsold copies can be returned to the publisher, less a restocking fee and shipping, for a net refund of $30. a) Based on the given information, Vaidy's conditional profits table for the bookstore is: Demand 75 P=0.30 65 P = 0.05 0000 70 P = 0.25 75 0.30 ☐☐☐☐ 80 0.15 00000 80 85 P = 0.15 P = 0.25 30000 85 0.25 ☐☐☐☐

Problem 3 Picante Corporation expects demand for mp3 players that they produce to increase. Demand for their mp3 players for last year was as follows: MONTH JANUARY FEBRUARY MARCH APRIL 2,150 2,000 2,200 AUGUST SEPTEMBER OCTOBER 2,450 2,700 2,850 DEMAND 2,100 MONTH JULY DEMAND 2,650 MAY JUNE 2,500 2,350 NOVEMBER DECEMBER 3,150 3,000 a. Using least squares regression analysis, what would you estimate demand to be for each month next year? b. To be reasonably confident of meeting demand, Picante Corporation decides to use three standard errors of estimate for safety. How many additional units should be held to meet this level of confidence?