The data below represents the quarterly changes in demand for a product over thenext 3 months.QuarterDemandQuarterDemandQuarterDemand112051649.18015815510199316471581117241608.16312170Apply the following forecasting techniques of the data to estimate the demand inperiod 13:a. Regression;b. Moving average with base m=3;c. Exponential smoothing with a = 0.1.

Answered: The data below represents the quarterly…

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 help with the correct answers in details: Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 3 4 5 6 Value 19 12 17 10 18 15 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error MAE = (b) mean squared error MSE = (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE = % (d) What is the forecast for week 7?
Use exponential smoothing with trend adjustment to forecast demand for period 11. Let α = 0.5, � = 0.3, and let the initial trend value be 12 and the initial forecast be 200
The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as follows: YEAR CASES OF MERLOT WINE 1 270 2 356 3 398 4 456 5 358 6 500 7 410 8 376 Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value calculated as of the end of year 8. Use the average demand for years 1 through 3 as your initial forecast for year 4, and then smooth the forecast forward to year 8. Note: Round your intermediate calculations and final answer to the nearest whole number.
The following table shows predicted product demand using your particular forecasting method along with the actual demand that occurred: FORECAST ACTUAL 1,480 1,530 1,380 1,480 1,680 1,580 1,730 1,780 1,630 1,680 Compute the tracking signal using the mean absolute deviation and running sum of forecast errors. Note: Negative values should be indicated by a minus sign. Round your "Mean Absolute Deviation", "Tracking Signal" to 2 decimal places and all other answers to the nearest whole number. Period Forecast Actual Deviation RSFE Absolute Deviation Sum of Absolute MAD TS Deviation 1 1,480 1,530 -50 -50 50 50 50.00 -1.00 2 1,380 1,480 -100 -150 100 150 75.00 -2.00 3 1,680 1,580 100 -50 100 250 83.33 -0.60 4 1,730 1,630 100 50 100 350 87.50 0.57 5 1,780 1,680 100 150 100 450 90.00 1.67
The following shows five months forecast demand and the corresponding actual demand for certain product.
The Yummy Ice Cream Company projects the demand for ice cream by using first-order exponential smoothing. Last week the forecast was 100,000 gallons of ice cream, and 90,000 gallons was actually sold. Using alpha=.1, prepare a forecast for next week. Calculate the forecast using Alpha=.2 and Alpha=.3 for this problem. Which values of Alpha gave the best forecast, assuming actual demand for next week ends up being 95,000 gallons?
Here are the actual tabulated demands for an item for a nine-month period (January through September). Your supervisor wants to test two forecasting methods to see which method was better over this period. MONTH ACTUAL January 120 February 145 March 146 April 171 May 154 June 182 July 138 August 135 September 146 a. Forecast April through September using a three-month moving average. b. Use simple exponential smoothing with an alpha of 0.20 to estimate April through September, using the average of January through March as the initial forecast for April. c-1. Calculate MAD for Three-month moving average and Exponential smoothing. c-2. Use MAD to decide which method produced the better forecast over the six-month period.
Give typed explanation Part 2: Using exponential smoothing, the forecasted demand for period 5 using the smoothing constant determined in image= ?
The following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 6 8 4 7 11 7 13 12 10 13 8 This exercise contains only parts b, c, and d. Part 2 b) Using the 3-year moving average, provide the forecast from periods 4 through 12 (round your responses to one decimal place). Part 3 c) Using the 3-year weighted moving average with weights 0.10, 0.30, and 0.60, using 0.60 for the most recent period, provide the forecast from periods 4 through 12 (round your responses to two decimal places). Part 4 d) Mean absolute deviation for the forecast developed…
The following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 7 9 6 10 12 7 12 12 9 9 8 Part 2 Using exponential smoothing with α = 0.30 and a forecast for year 1 of 6.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place). Part 3 Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers).
Use exponential smoothing with trend adjustment to forecast deliveries for period 5. Let α = 0.1, β = 0.2, and let the initial trend value be 4 and the initial forecast be 200 (both are given in the table). (a) Complete the table below and to predict the demand for Period 5 (See image). Show the calculations for the demand for Period 2. (b) Based on the actual demands of the first 4 periods forecast the demand for period 5 using the linear regression method. (c) Which method performs better based on the actual demand for period 5? Why do you think so?
Cadbury started an in-depth study to forecast customer demand based on data it previously recorded. Management at the global brand started recording sales data in two forms: yearly, & quarterly. The following tables show the recorded data for the past five years: Year Actual Demand 2017 128 2018 148 2019 161 2020 149 2021 137 Quarter 2017 2018 2019 2020 2021 1 30 39 42 36 33 2 42 41 47 34 45 31 33 41 42 31 25 35 31 37 28 The forecasted demand for the 2nd Quarter of year 2022 is * 18.25 43.45 25.18 目目

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