10Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fokheach year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year:!1F1A1optionYearNumber of PatientsRobbery Rate per1,000 PopulationThe simple linear regression equation that shows the best relationship between the number of patients and the robbery rate is (round your responses to three decimal places):ŷ=0+0xN@2WSXcommandAwhere y Number of Patients and x = Robbery Rate.In year 11, if the robbery rate increases to 133.40, using trend analysis, the number of patients Dr. Fok will see = patients (round your response to two decimal places).In year 11, if the robbery rate decreases to 90.6, using trend analysis, the number of patients Dr. Fok will see =patients (round your response to two decimal places).#380F3ED$4C888F4RF5VFST13373958.0 61.1 73.4 75.2 78.5G^6MacBook AirB232*FoYH&745641 41 5644F7UN*8CCJwDil**FB79605889.5 99.6 94.8 104.1 115.6-M(- 09KDDF9OV-IH85426-0)asF10PTL. V3>4....Icommand option10F11{60[+ 112.1D=?400)F12}]Nextdelete1\returnsh

A statistical technique indeed known as simple linear regression enables us to analyze and explore…

Answered: Dr. Lillian Fok, a New Orleans…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 30P: A company manufacturers a product in the United States and sells it in England. The unit cost of...

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An automobile manufacturer is considering whether to introduce a new model called the Racer. The profitability of the Racer depends on the following factors: The fixed cost of developing the Racer is triangularly distributed with parameters 3, 4, and 5, all in billions. Year 1 sales are normally distributed with mean 200,000 and standard deviation 50,000. Year 2 sales are normally distributed with mean equal to actual year 1 sales and standard deviation 50,000. Year 3 sales are normally distributed with mean equal to actual year 2 sales and standard deviation 50,000. The selling price in year 1 is 25,000. The year 2 selling price will be 1.05[year 1 price + 50 (% diff1)] where % diff1 is the number of percentage points by which actual year 1 sales differ from expected year 1 sales. The 1.05 factor accounts for inflation. For example, if the year 1 sales figure is 180,000, which is 10 percentage points below the expected year 1 sales, then the year 2 price will be 1.05[25,000 + 50( 10)] = 25,725. Similarly, the year 3 price will be 1.05[year 2 price + 50(% diff2)] where % diff2 is the percentage by which actual year 2 sales differ from expected year 2 sales. The variable cost in year 1 is triangularly distributed with parameters 10,000, 12,000, and 15,000, and it is assumed to increase by 5% each year. Your goal is to estimate the NPV of the new car during its first three years. Assume that the company is able to produce exactly as many cars as it can sell. Also, assume that cash flows are discounted at 10%. Simulate 1000 trials to estimate the mean and standard deviation of the NPV for the first three years of sales. Also, determine an interval such that you are 95% certain that the NPV of the Racer during its first three years of operation will be within this interval.
A company manufacturers a product in the United States and sells it in England. The unit cost of manufacturing is 50. The current exchange rate (dollars per pound) is 1.221. The demand function, which indicates how many units the company can sell in England as a function of price (in pounds) is of the power type, with constant 27556759 and exponent 2.4. a. Develop a model for the companys profit (in dollars) as a function of the price it charges (in pounds). Then use a data table to find the profit-maximizing price to the nearest pound. b. If the exchange rate varies from its current value, does the profit-maximizing price increase or decrease? Does the maximum profit increase or decrease?
The eTech Company is a fairly recent entry in the electronic device area. The company competes with Apple. Samsung, and other well-known companies in the manufacturing and sales of personal handheld devices. Although eTech recognizes that it is a niche player and will likely remain so in the foreseeable future, it is trying to increase its current small market share in this huge competitive market. Jim Simons, VP of Production, and Catherine Dolans, VP of Marketing, have been discussing the possible addition of a new product to the companys current (rather limited) product line. The tentative name for this new product is ePlayerX. Jim and Catherine agree that the ePlayerX, which will feature a sleeker design and more memory, is necessary to compete successfully with the big boys, but they are also worried that the ePlayerX could cannibalize sales of their existing productsand that it could even detract from their bottom line. They must eventually decide how much to spend to develop and manufacture the ePlayerX and how aggressively to market it. Depending on these decisions, they must forecast demand for the ePlayerX, as well as sales for their existing products. They also realize that Apple. Samsung, and the other big players are not standing still. These competitors could introduce their own new products, which could have very negative effects on demand for the ePlayerX. The expected timeline for the ePlayerX is that development will take no more than a year to complete and that the product will be introduced in the market a year from now. Jim and Catherine are aware that there are lots of decisions to make and lots of uncertainties involved, but they need to start somewhere. To this end. Jim and Catherine have decided to base their decisions on a planning horizon of four years, including the development year. They realize that the personal handheld device market is very fluid, with updates to existing products occurring almost continuously. However, they believe they can include such considerations into their cost, revenue, and demand estimates, and that a four-year planning horizon makes sense. In addition, they have identified the following problem parameters. (In this first pass, all distinctions are binary: low-end or high-end, small-effect or large-effect, and so on.) In the absence of cannibalization, the sales of existing eTech products are expected to produce year I net revenues of 10 million, and the forecast of the annual increase in net revenues is 2%. The ePIayerX will be developed as either a low-end or a high-end product, with corresponding fixed development costs (1.5 million or 2.5 million), variable manufacturing costs ( 100 or 200). and selling prices (150 or 300). The fixed development cost is incurred now, at the beginning of year I, and the variable cost and selling price are assumed to remain constant throughout the planning horizon. The new product will be marketed either mildly aggressively or very aggressively, with corresponding costs. The costs of a mildly aggressive marketing campaign are 1.5 million in year 1 and 0.5 million annually in years 2 to 4. For a very aggressive campaign, these costs increase to 3.5 million and 1.5 million, respectively. (These marketing costs are not part of the variable cost mentioned in the previous bullet; they are separate.) Depending on whether the ePlayerX is a low-end or high-end produce the level of the ePlayerXs cannibalization rate of existing eTech products will be either low (10%) or high (20%). Each cannibalization rate affects only sales of existing products in years 2 to 4, not year I sales. For example, if the cannibalization rate is 10%, then sales of existing products in each of years 2 to 4 will be 10% below their projected values without cannibalization. A base case forecast of demand for the ePlayerX is that in its first year on the market, year 2, demand will be for 100,000 units, and then demand will increase by 5% annually in years 3 and 4. This base forecast is based on a low-end version of the ePlayerX and mildly aggressive marketing. It will be adjusted for a high-end will product, aggressive marketing, and competitor behavior. The adjustments with no competing product appear in Table 2.3. The adjustments with a competing product appear in Table 2.4. Each adjustment is to demand for the ePlayerX in each of years 2 to 4. For example, if the adjustment is 10%, then demand in each of years 2 to 4 will be 10% lower than it would have been in the base case. Demand and units sold are the samethat is, eTech will produce exactly what its customers demand so that no inventory or backorders will occur. Table 2.3 Demand Adjustments When No Competing Product Is Introduced Table 2.4 Demand Adjustments When a Competing Product Is Introduced Because Jim and Catherine are approaching the day when they will be sharing their plans with other company executives, they have asked you to prepare an Excel spreadsheet model that will answer the many what-if questions they expect to be asked. Specifically, they have asked you to do the following: You should enter all of the given data in an inputs section with clear labeling and appropriate number formatting. If you believe that any explanations are required, you can enter them in text boxes or cell comments. In this section and in the rest of the model, all monetary values (other than the variable cost and the selling price) should be expressed in millions of dollars, and all demands for the ePlayerX should be expressed in thousands of units. You should have a scenario section that contains a 0/1 variable for each of the binary options discussed here. For example, one of these should be 0 if the low-end product is chosen and it should be 1 if the high-end product is chosen. You should have a parameters section that contains the values of the various parameters listed in the case, depending on the values of the 0/1 variables in the previous bullet For example, the fixed development cost will be 1.5 million or 2.5 million depending on whether the 0/1 variable in the previous bullet is 0 or 1, and this can be calculated with a simple IF formula. You can decide how to implement the IF logic for the various parameters. You should have a cash flows section that calculates the annual cash flows for the four-year period. These cash flows include the net revenues from existing products, the marketing costs for ePlayerX, and the net revenues for sales of ePlayerX (To calculate these latter values, it will help to have a row for annual units sold of ePlayerX.) The cash flows should also include depreciation on the fixed development cost, calculated on a straight-line four-year basis (that is. 25% of the cost in each of the four years). Then, these annual revenues/costs should be summed for each year to get net cash flow before taxes, taxes should be calculated using a 32% tax rate, and taxes should be subtracted and depreciation should be added back in to get net cash flows after taxes. (The point is that depreciation is first subtracted, because it is not taxed, but then it is added back in after taxes have been calculated.) You should calculate the company's NPV for the four-year horizon using a discount rate of 10%. You can assume that the fixed development cost is incurred now. so that it is not discounted, and that all other costs and revenues are incurred at the ends of the respective years. You should accompany all of this with a line chart with three series: annual net revenues from existing products; annual marketing costs for ePlayerX; and annual net revenues from sales of ePlayerX. Once all of this is completed. Jim and Catherine will have a powerful tool for presentation purposes. By adjusting the 0/1 scenario variables, their audience will be able to see immediately, both numerically and graphically, the financial consequences of various scenarios.
A motion picture industry analyst is studying movies based on epic novels. The following data were obtained for 10 Hollywood movies made in the past five years. Each movie was based on an epic novel. For these data, x1 = first-year box office receipts of the movie, x2 = total production costs of the movie, x3 = total promotional costs of the movie, and x4 = total book sales prior to movie release. All units are in millions of dollars. x1 x2 x3 x4 85.1 8.5 5.1 4.7 106.3 12.9 5.8 8.8 50.2 5.2 2.1 15.1 130.6 10.7 8.4 12.2 54.8 3.1 2.9 10.6 30.3 3.5 1.2 3.5 79.4 9.2 3.7 9.7 91.0 9.0 7.6 5.9 135.4 15.1 7.7 20.8 89.3 10.2 4.5 7.9 a) Suppose Hollywood is planning a new epic movie with projected box office sales x1 = 100 million and production costs x2 = 12 million. The book on which the movie is based had sales of x4 = 9.2 million. Forecast the dollar amount (in millions) that should be budgeted for promotion costs x3 and find an 80% confidence interval for your…
The following data is given x 0.2 0.5 1 2 3 y 3 2 1.4 1 0.6 Using the transformed linear regression, which are m and b in the function 1/(mx+b) ? Group of answer choices m=0.5842, b=0.4 m=0.4488, b=0.2415 m=1.5, b=2.5 m=1, b=2.4 m=0.8173, b=0.4450
The U.S. pharmaceutical market is the largest in the world in which it generated over 530 billion U.S. dollars in 2020. The industry sales growth rate is expected to continue growing, and it will be worth 685.45 billion U.S. dollars by 2023. Johnson & Johnson (J&J) is the current market leader in the U.S. pharmaceutical industry and its market share increased by 7.89% in 2020. After applying the BCG Matrix, the CEO of J&J found that the pharmaceutical segment generates the majority of his company’s sales. Therefore, he decided to allocate more capital to research and development in this segment. He is particularly interested in enhancing the effectiveness of their Janssen COVID-19 vaccine. Which of the following strategies did the CEO of J&J decide to pursue? * Market developmentProduct DevelopmentHorizontal IntegrationMarket penetration
Integrated Products Corporation (IPC) needs to estimate its PC sales for next year.The most recent six years of revenue data for the company’s line of XT PersonalComputers, and those of the industry, is found in the table below:Year XT PC Sales Revenue($’000,000)All Industry PC Sales Revenue($’000,000,000)1 2.4 4.62 5.9 8.63 15.5 10.74 27.8 14.85 35.9 18.56 38.1 19.4Required:A. Assuming that the sales data above are representative of sales expected nextyear, use time series regression analysis to forecast next year’s sales revenues(there is no seasonal effect).B. Perform a regression analysis between the annual sales revenues of XTPersonal Computers and all industry PC annual sales revenues. What is theforecast for next year’s sales revenue for XT Personal Computers if the estimateof next year’s industry PC sales revenues is $21.9 billion? C. Advise management at Integrated Products Corporation (IPC) which of the twosales estimates from parts A and B above they should use. Justify your…
Integrated Products Corporation (IPC) needs to estimate its PC sales for next year.The most recent six years of revenue data for the company’s line of XT PersonalComputers, and those of the industry, is found in the table below:Year XT PC Sales Revenue($’000,000)All Industry PC Sales Revenue($’000,000,000)1 2.4 4.62 5.9 8.63 15.5 10.74 27.8 14.85 35.9 18.56 38.1 19.4Required:A. Assuming that the sales data above are representative of sales expected nextyear, use time series regression analysis to forecast next year’s sales revenues(there is no seasonal effect).B. Perform a regression analysis between the annual sales revenues of XTPersonal Computers and all industry PC annual sales revenues. What is theforecast for next year’s sales revenue for XT Personal Computers if the estimateof next year’s industry PC sales revenues is $21.9 billion?
solve a and b The following table shows the rank attained by male and female officers in the NewYork City Police Department (NYPD).a) Do these data indicate that men and women are equitably represented at all levelsof the department? Test using a p-value approach. Male FemaleOfficer 21,900 4281Detective 4058 806Sergeant 3898 415Lieutenant 1333 89Captain 359 12Higher ranks 218 10 b) There are far more men than women in the police force in general. However, the NYCPolice Commission has set itself certain goals with respect to the positions of the femalesamong its ranks. Across the females they aim to target the same proportion by rank asthey do among the males. The target proportions by category are:(1) Officer – 70% (2) Detectives – 15% (3) Sargent – 10%(4) Lieutenant – 3% (5) Captain – 1% (6) Higher – 1%Conduct a test to determine whether the proportions,…
The table below shows the sales figures for a brand of shoe over the last 12 months.Months SalesJanuary 69February 75March 86April 92May 95June 100July 108August 115September 125October 131November 140December 150a. Using the following, forecast the sales for the months up to January the following year:-i. A simple three month moving average. ii. A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data. iii. Exponential Smoothing when α= .6 and the forecast for March is 350.iv. Determine which of the three forecasting technique is the most accurate using MAD.
The number of auto accidents in Athens, Ohio is related to the regional number of regisgtered automobiles in thousands (X1) alcholic beverage sales in $10,000 (X2) and rainfall in inches (X3). Furthermore the regression formula has been calculated as: y=a+b1X1+b2x2+b3X3 where y= number of automobile accidents a= 8.0 b1= 3.5 b2=5.0 b3= 2.4 For the given values of X1,X2, and X3, the expected number of accidents will be ( round your responses to one decimal place) X1 X2 X3 # of accidents 6.0 7.0 0.0 [__]
Dr. Lillian Fok, a New Orleans psychologist, spe-cializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how manypatients Dr. Fok has seen each year for the past 10 years. It alsoindicates what the robbery rate was in New Orleans during thesame year: Using trend (linear regression) analysis, predict the number ofpatients Dr. Fok will see in years 11 and 12 as a function of time.How well does the model fit the data?

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