Assume the weight is 0.6 for the most recent period; 0.2 for the second most recent; 0.1 for the third most recent; and 0.1 for the fourth most recent period. Using the four-period weighted moving average technique to predict the demand in February 2019. Find the X and Y values. Dt Ft Period Demand Four-period weighted Moving Average 2014 September 9400 October 10300 November 11200 December 4998 2015 January 9800 7209 February 9555 X March 9800 Y Group of answer choices X = 9899.8; Y = 9778.2 X = 9312.8; Y = 9555.2 X = 9029.6; Y = 9312.8 X = 9555.0; Y = 9313.7 X = 9872.4; Y = 9029.4

Assume the weight is 0.6 for the most recent period; 0.2 for the second most recent; 0.1 for the third most recent; and 0.1 for the fourth most recent period. Using the four-period weighted moving average technique to predict the demand in February 2019. Find the X and Y values. Dt Ft Period Demand Four-period weighted Moving Average 2014 September 9400 October 10300 November 11200 December 4998 2015 January 9800 7209 February 9555 X March 9800 Y Group of answer choices X = 9899.8; Y = 9778.2 X = 9312.8; Y = 9555.2 X = 9029.6; Y = 9312.8 X = 9555.0; Y = 9313.7 X = 9872.4; Y = 9029.4

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 40P

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Sometimes curvature in a scatterplot can be fit adequately (especially to the naked eye) by several trend lines. We discussed the exponential trend line, and the power trend line is discussed in the previous problem. Still another fairly simple trend line is the parabola, a polynomial of order 2 (also called a quadratic). For the demand-price data in the file P13_10.xlsx, fit all three of these types of trend lines to the data, and calculate the MAPE for each. Which provides the best fit? (Hint: Note that a polynomial of order 2 is still another of Excels Trend line options.)
Assume the demand for a companys drug Wozac during the current year is 50,000, and assume demand will grow at 5% a year. If the company builds a plant that can produce x units of Wozac per year, it will cost 16x. Each unit of Wozac is sold for 3. Each unit of Wozac produced incurs a variable production cost of 0.20. It costs 0.40 per year to operate a unit of capacity. Determine how large a Wozac plant the company should build to maximize its expected profit over the next 10 years.
Play Things is developing a new Lady Gaga doll. The company has made the following assumptions: The doll will sell for a random number of years from 1 to 10. Each of these 10 possibilities is equally likely. At the beginning of year 1, the potential market for the doll is two million. The potential market grows by an average of 4% per year. The company is 95% sure that the growth in the potential market during any year will be between 2.5% and 5.5%. It uses a normal distribution to model this. The company believes its share of the potential market during year 1 will be at worst 30%, most likely 50%, and at best 60%. It uses a triangular distribution to model this. The variable cost of producing a doll during year 1 has a triangular distribution with parameters 15, 17, and 20. The current selling price is 45. Each year, the variable cost of producing the doll will increase by an amount that is triangularly distributed with parameters 2.5%, 3%, and 3.5%. You can assume that once this change is generated, it will be the same for each year. You can also assume that the company will change its selling price by the same percentage each year. The fixed cost of developing the doll (which is incurred right away, at time 0) has a triangular distribution with parameters 5 million, 7.5 million, and 12 million. Right now there is one competitor in the market. During each year that begins with four or fewer competitors, there is a 25% chance that a new competitor will enter the market. Year t sales (for t 1) are determined as follows. Suppose that at the end of year t 1, n competitors are present (including Play Things). Then during year t, a fraction 0.9 0.1n of the company's loyal customers (last year's purchasers) will buy a doll from Play Things this year, and a fraction 0.2 0.04n of customers currently in the market ho did not purchase a doll last year will purchase a doll from Play Things this year. Adding these two provides the mean sales for this year. Then the actual sales this year is normally distributed with this mean and standard deviation equal to 7.5% of the mean. a. Use @RISK to estimate the expected NPV of this project. b. Use the percentiles in @ RISKs output to find an interval such that you are 95% certain that the companys actual NPV will be within this interval.
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The Saki motorcycle dealer in the Minneapolis–St. Paul area wants to make an accurate forecast of demand for the Saki Super TXII motorcycle during the next month. Because the manufacturer is in Japan, it is difficult to send motorcycles back or reorder if the proper number is not ordered a month ahead. From sales records, the dealer has accumulated the following data for the past year: Month Motorcycle Sales January 9 February 7 March 10 April 8 May 7 June 12 July 10 August 11 September 12 October 10 November 14 December 16 a. Compute a 3-month moving average forecast of demand for April through January (of the next year). b. Compute a 5-month moving average forecast for June through January. c. Compare the two forecasts computed in (a) and (b), using MAD. Which one should the dealer use for January of the next year?
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The Victory Plus Mutual Fund of growth stocks has had the following average monthly price forthe past 10 months:Month Fund Price1 62.72 63.93 68.04 66.45 67.26 65.87 68.28 69.39 67.210 70.1Compute the exponentially smoothed forecast with a = .40 the adjusted exponential smoothing forecastwith a = .40 and B=30 and the linear trend line forecast. Compare the accuracy of the threeforecasts, using cumulative error and MAD, and indicate which forecast appears to be most accurate.
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		Dt	Ft
	Period	Demand	Four-period weighted Moving Average
2014	September	9400
	October	10300
	November	11200
	December	4998
2015	January	9800	7209
	February	9555	X
	March	9800	Y