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Grand Canyon MGt455 module 3 problems




Question;Problem set 3;Mgt-455;Complete problems 4.1, 4.3;4.5, 4.27, 4.31., and 4.37 in the textbook.;Please ensure that the Excel file;includes the associated cell computations, this information is needed in order;to receive full credit for these problems.;Note;PXmeans the problem may be solved with POM for Windows and/or Excel OM.;4.1;The following gives the number of pints of type B;blood used at Woodlawn Hospital in the past 6 weeks;WEEK OF PINTS USED;Weeks of pints;used;August 31 360;September 7 389;September 14 410;September 21 381;September 28 368;October 5 374;a) Forecast the demand for the week of October 12 using a;3-week moving average.;b) Use a 3-week weighted moving average, with weights of.1,.3;and.6, using.6 for the most recent week. Forecast demand for;the week of October 12.;c) Compute the forecast for the week of October 12 using;exponential;smoothing with a forecast for August 31 of 360 and a 5.2. PX;4.2;year 1 2;3 4 5;6 7 8;9 10 11;demand 7 9;5 9 13;8 12 13;9 11 7;a) Plot the above data on a graph. Do you observe any trend;cycles, or random variations?;b) Starting in year 4 and going to year 12, forecast demand using;a 3-year moving average. Plot your forecast on the same graph;as the original data.;c) Starting in year 4 and going to year 12, forecast demand using;a 3-year moving average with weights of.1,.3, and.6, using.6;for the most recent year. Plot this forecast on the same graph.;d) As you compare forecasts with the original data, which seems;to give the better results? PX;4.3;Refer to Problem 4.2.;Develop a forecast for years 2;through 12 using exponential smoothing with a 5.4 and a forecast;for year 1 of 6. Plot your new forecast on a graph with the;actual data and the naive forecast. Based on a visual inspection;which forecast is better? PX;4.5;The Carbondale Hospital is;considering the purchase;of a new ambulance. The decision will rest partly on the;anticipated;mileage to be driven next year. The miles driven during the;past 5 years are as follows;year mileage;1 3,000;2 4,000;3 3,400;4 3,800;5 3,700;a);Forecast the mileage for next year (6th year) using a 2-year;moving;average.;b);Find the MAD based on the 2-year moving average. (Hint;You;will have only 3 years of matched data.);c);Use a weighted 2-year moving average with weights of.4;and;.6 to forecast next year?s mileage. (The weight of.6 is;for;the most recent year.) What MAD results from using this;approach;to forecasting? (Hint: You will have only 3 years of;matched;data.);d);Compute the forecast for year 6 using exponential smoothing;an;initial forecast for year 1 of 3,000 miles, and a 5.5. PX;4.27;George;Kyparisis owns a company that manufactures;sailboats.;Actual demand for George?s sailboats during each of;the;past four seasons was as follows;year;season 1 2 3 4;winter 1400 1200 1000 900;spring 1500 1400 1600 1500;summer 1000 2100 2000 1900;fall 600 750 650 500;George;has forecasted that annual demand for his sailboats;in;year 5 will equal 5,600 sailboats. Based on this data and the;multiplicative;seasonal model, what will the demand level be for;George?s;sailboats in the spring of year 5?;4.31;Caf.;Michigan?s manager, Gary Stark, suspects;that;demand for mocha latte coffees depends on the price being;charged.;Based on historical observations, Gary has gathered the;following;data, which show the numbers of these coffees sold over;six;different price values;price number sold;$2.30 760;$3.50 510;$2.00 980;$4.20 250;$3.10 320;$4.05 480;Using;these data, how many mocha latte coffees would be forecast;to;be sold according to simple linear regression if the price;per;cup were $2.80? PX;4.37;Sales;of tablet computers at Ted Glickman?s electronics;store;in Washington, D.C., over the past 10 weeks are shown;in;the table below;weekdemand weekdemand;1 20 6 29;2 21 7 36;3 28 8 22;4 37 9 25;5 25 10 28;a);Forecast demand for each week, including week 10, using;exponential;smoothing with a =.5 (initial forecast 5 20).;b);Compute the MAD.;c);Compute the tracking signal. PX


Paper#60864 | Written in 18-Jul-2015

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