KThe actual number of patients at Providence Emergency Medical Clinic for the first six weeks of this year follows:Week123456OA. The value of the forecast will remain the same.B. The value of the forecast will increase.OC. The value of the forecast will decrease.Actual No. of Patients272936202435Clinic administrator Dana Schniederjans wants you to forecast patient numbers at the clinic for week 7 by using this data. You decide to use a weighted moving average method to find this forecast. Your methoduses four actual demand levels, with weights of 0.333 on the present period, 0.250 one period ago, 0.250 two periods ago, and 0.167 three periods ago.a) What is the value of your forecast?The value of the forecast is 28.67 patients (round your response to two decimal places).b) If instead the weights were 20, 15, 15, and 10, respectively, how would the forecast change?

Forecasting is a technique used to predict future outcomes on the basis of past data. In businesses…

Answered: Clinic administrator Dana Schniederjans…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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4 Trinity General Hospital had the following number of patient admissions during the past 8 weeks Patient Week Admissions 1 120 145 3 95 4 112 5 130 6. 110 7 100 140 Develop a 3-weck weighted average forecast for Week 4 through 9 with weights a W1 = 0.2 W2 = 0.3 W3 = 0.5 Forecast patient admissions for week 9 using simple | exponential smoothing with a = 0.2. Assume that the forecast for Week 2 (F2) is the naïve forecast.
Sales of tablet computers at Marika Gonzalez's electronics store in Washington, D.C., over the past 10 weeks are shown in the table below: Week 2 3 1 Demand 19 23 29 4 36 5 6 7 8 9 10 26 28 35 24 24 30 a) The forecast for weeks 2 through 10 using exponential smoothing with a = 0.60 and a week 1 initial forecast of 19.0 are (round your responses to two decimal places): Week 1 2 3 4 Demand 19 23 29 36 Forecast 19.0 5 6 7 26 28 35 8 9 10 24 30 24 b) For the forecast developed using exponential smoothing (a=0.60 and initial forecast 19.0), the MAD = sales (round your response to two decimal places). c) For the forecast developed using exponential smoothing (x=0.60 and initial forecast 19,0), the tracking signal = (round your response to two decimal places).
The actual monthly demand of special pizza in the past 6 months were: 392, 355, 406, 427, 282, 394 If a four-month moving average forecasting model is used to generate forecasts, what is the value of the Mean Absolute Percent Error (in percent)? Use at least 4 decimals.
) Consider the following time series data: Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 i)Construct a time series plot. What type of pattern exist in the data? ii)Develop a three – week moving average for the time series. Compute MSE and a forecast cast for week 7. Use alpha = 0.2 to compute the exponential smoothing value for the time series. Compute MSE and a forecast for week 7. IV)Compare the three -week moving average forecast with exponential smoothing forecast using alpha = 0.2. Which appears to provide the better forecast based on MSE? Explain V)Use trial and error to find a value of the exponential smoothing. Coefficient Alpha that result in a smaller MSE than what you calculated for alpha = 0.2.
Forecast sales for the 11th period. For leveling, use exponential smoothing 0.20 and moving average 3 for averaging; and linear and exponential functions for trend data. Assume an initial exponential forecast of 620 units in period 2 if you decide to use it (i.e., no forecast for period 1). Period 1 2 4 5. 17 8. 6. 10 Sales 748 690 731 869 845 956 1200 1062 1090 1200
Clinic administrator Marc Schniederjans wants you to forecastpatient demand at the clinic for week 7 by using this data. You decide to use a weighted moving average method to find this fore-cast. Your method uses four actual demand levels, with weights of 0.333 on the present period, 0.25 one period ago, 0.25 two peri-ods ago, and 0.167 three periods ago. a) What is the value of your forecast? PXb) If instead the weights were 20, 15, 15, and 10, respectively, howwould the forecast change? Explain why. c) What if the weights were 0.40, 0.30, 0.20, and 0.10, respec-tively? Now what is the forecast for week 7?
At the ABC Floral Shop, an argument developed between two of the owners, Bob and Henry, over the accuracy of forecasting methods. Bob argued that exponential smoothing with α = .1 would be the best method. Henry argued that the shop would get a better forecast with α = .3.a. Using F1 = 100 and the data from problem 3, which of the two managers is right?b. Graph the two forecasts and the original data using Excel. What does the graph reveal?c. Maybe forecast accuracy could be improved. Try additional values of α = .2, .4, and .5 to see if better accuracy is achieved.
An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the naive approach. The linear trend equation is Ft = 124 + 2.1t, and it was developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy if MAD and MSE are used? (Round your intermediate calculations and final answers to 2 decimal places.) Units Sold 11 144 146 13 152 14 142 15 152 16 149 17 152 18 154 19 157 20 164 Click here for the Excel Data File MAD (Naive) 5.11 MAD (Linear) MSE (Naive) MSE (Linear) provides forecasts with less average error and less average squared error. H N M 4 56 r 00
Step 1 of 4: Determine the three-period moving average for the next time period. If necessary, round your answer to one decimal place. Step 2 of 4: Determine the three-period weighted moving average for the next time period with weights of 33 (most recent), 22 (second latest time period), and 11 (oldest time period). If necessary, round your answer to one decimal place. Step 3 of 4: Determine the exponential smoothing forecast for the next time period using a smoothing constant of 0.500.50. If necessary, round your answer to one decimal place. Step 4 of 4: Which forecasting method is best and why?
Sales of tablet computers at Marika Gonzalez's electronics store in Washington, D.C., over the past 10 weeks are shown in the table below: Week Demand 1 20 2 20 Week 1 Demand 20 Forecast 20.0 3 29 4 37 4 37 5 24 2 3 29 20 6 30 7 8 37 24 a) The forecast for weeks 2 through 10 using exponential smoothing with a = 0.55 and a week 1 initial forecast of 20.0 are (round your responses to two decimal places): 5 6 30 24 7 37 9 24 8 24 10 28 9 24 10 28
What should be our forecast accuracy target if there is a high degree of volatility in customer orders and long lead times? We have a new chief sales officer who is proposing that we should forecast in dollars, not in units/cases. I have never heard of anyone forecasting in dollars. It is true that dollarized forecasts can help Sales in knowing precisely what sales target they should be hitting. But, is it the best practice?
- 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: 6 10 Week 1 Demand 20 2 3 23 27 4 5 37 26 7 8 9 30 35 22 24 29 a) The forecast for weeks 2 through 10 using exponential smoothing with a = 0.55 and a week 1 initial forecast of 20.0 are (round your responses to two decimal places): Week 1 Demand 20 Forecast 20.0 2 3 23 27 4 37 5 26 6 30 7 35 8 22 9 24 10 29

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