3. Attendance at Los Angeles' newest Disney like attraction, Vacation World has been asfollows:QuarterGuestsQuarterGuests(in Thousands)(in Thousands)2017 Q173Q3124Q2104Q452Q31682019 Q189Q474Q21462018 Q165Q3205Q282Q498a. Graph the data. (Use Excel)b. Compute seasonal indices using all the data. (Solve manually)

A seasonal index measures the values/changes of a particular season of a cycle compared to the…

Answered: Graph the data. (Use Excel) b. Compute…

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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please answer in excel Jean’s Copiers sells and repairs photocopy machines. The manager needs weekly forecasts of service calls so that she can schedule the personnel. The manager uses α = 0.3 for exponential smoothing, and the forecast for the first week was 24 calls. The manager also uses 3 weekly moving averages technique. a) Using 3 period moving averages, forecast the number of calls for week 7. b) Using exponential smoothing, forecast the number of calls for week 7. c) Compare these two forecasting techniques using Mean Squared Errors (MSE) measure. Which one is better?
Forecast error is calculated as: Actual - Forecast O Forecast - Actual (Forecast - Actual) ^ 2 Absolute (Actual - Forecast) (Actual - Forecast) ^ 2
Respond to each of the items using the following time series data. Period Demand 144 2 172 3 157 4 160 144 181 7 160 8 176 9. 149 10 183 11 182 12 149 13 153 14 164 15 153 16 104 Click here for the Excel Data File b. Compute all possible forecasts using a five-period moving average. (Round your answers to 1 decimal place.) Absolute Period Demand 5-period SMA Errors 1 144 172 3 157 4. 160 5 144 181 7 160 8 176 9 149 10 183 11 182 12 149 13 153 14 164 LO
a. What is the mean square error for time periods 2 through 4 using the average forecasting method? b. What is the mean absolute error for time periods 2 through 4 using the average forecasting method? c. What is the mean absolute percentage error for time period 2 through 4 using the average forecasting method? Round all answers to two decimal places. Time Period 1 2 3 4 Mean absolute error (MAE) Mean squared error (MSE) Mean absolute percentage error (MAPE) Electric Bill 510 315 420 480 Average Forecast Forecast Error
b. Prepare forecasts for June through September by using an exponential smoothing model with α = 0.4. Assume that the forecast for May was 2,100 (enter your responses rounded to the nearest whole number). Month March April May June July August September March April May June Demand Demand 120 2,030 1,110 4,210 3,260 5,830 c. Prepare forecasts for June through September by using an adjusted exponential smoothing model with α = 0.4 and ß = 0.2. Assume that the unadjusted forecast for May was 2,100 and the trend factor T₁ for May was 900 (enter your responses rounded to the nearest whole number). Month 120 2,030 1,110 4,210 Forecast 2,100 1704 2707 2928 4089 2,100 1,704 Unadjusted forecast Adjusted forecast
January February March April May June a. Calculate forecasts for the remaining five months using simple exponential smoothing with a = 0.4. February March April May June ACTUAL FORECAST 100 85 96 103 82 66 90 MAD Forecasts 91 93 97 91 81 b. Calculate the MAD for all the forecasts, including January's. (Round your answer to 1 decimal place.)
The Toro Cutlery Company has collected monthly sales information below: MONTH January February March April The company is examining two forecasting methods, moving average and exponential smoothing for forecasting sales. a. What will the forecast be for January the following year using a three-, four-, and five-month moving averages? Do not round intermediate calculations. Round your answers to the nearest whole number. Forecast (January, 3-month MA): 87667 Forecast (January, 4-month MA): 72500 Forecast (January, 5-month MA): 69600 b. What will the forecast be for January the following year using exponential smoothing with a = 0.6? Assume the forecast for February this year is 25,000. Do not round intermediate calculations. Round your answer to the nearest whole number. SALES 25,000 18,000 43,000 110,000 MONTH May June July August SALES MONTH 84,000 September 28,000 October 97,000 November 58,000 December SALES 27,000 105,000 82,000 76,000
Given the following sales data: week 1: 203 week 2: 185 week 3: 164 week 4: 151 week 5: 115 Forecast sales for week 6 using Holt's model with: alpha = 0.3 beta = 0.4 Use L(2) = A(2) and T(2) = A(2) - A(1) to initialize the model. %3D Your Answer: Answer
1. The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Part 2 Week Of Pints Used August 31 350 September 7 372 September 14 412 September 21 381 September 28 366 October 5 378 Part 3 a) The forecasted demand for the week of October 12 using a 3-week moving average LOADING... = _____________pints (round your response to two decimal places).
Which of the following is not a step in the forecasting process? O a. select a forecasting model O b. eliminate all assumptions O c. determine the purpose and level of detail required O d. establish a time horizon O e. monitor the forecast GE 321
Part C Exponential Exponential Gasoline Demand Gasoline Month smoothed forecast smoothed forecast Exponential smoothed forecast (a = 0.25) Demand (a = 0.25) (a = 0.45) Exponential smoothed forecast (a = 0.45) Mar 900 920 920 1200 Apr May 755 915.00 911.00 1100 1000 650 875.00 840.80 g20 915.00 846 80 755 818.75 754.94 904.76 835.12 Jun 550 818.75 754.94 800 320 751.56 66272 645.74 746.83 Jul 625 751.56 662.72 650 600 550 Aug Sep 730 719.92 645.74 820 722.44 683.66 400 D Oct 1100 746.83 745.01 200 1 Nov 835.12 904.76 Mar Apr May Jun Jul Aug Sep Oct Nov 1. Make a comparative analysis out of your answers in the plotted data. (3-5 5 sentences)
Please do not give solution in image formate thanku. Bradley's Copiers sells and repairs photocopy machines. The manager needs weekly forecasts of service calls so that he can schedule service personnel. Use the actual demand in the first period for the forecast for the first week so error measurement begins in the second week. The manager uses exponential smoothing with α = 0.5 Forecast the number of calls for week 6, which is next week. WEEK ACTUAL SERVICE CALLS 1 28 2 32 3 40 4 27 5 30

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Graph the data. (Use Excel) b. Compute seasonal indices using all the data. (Solve manually) а.