Income at the law firm of Smith and Jones for the period February to July was as follows:MonthFebruary MarchAprilMayJuneJulyIncome (in $ thousand)90.091.596.085.492.296.0Assume that the initial forecast for February is $85,000 and the initial trend adjustment is 0. The smoothing constantsselected are a = 0.1 and ß = 0.2. Using trend-adjusted exponential smoothing, the forecast for the law firm's Augustincome =O thousand dollars (round your response to two decimal places).

Unadjusted forecast = alpha*actual income of previous period+(1-alpha)*forecast of the previous…

Answered: Assume that the initial forecast for…

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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The following monthly sales of chocolate boxes (in thousands of AUS dollars) have been recorded for January, February, March, and April, respectively: 9.5, 8, 9, 9. Examining the forecasting accuracy for the month of April only: Explain which of the following forecasting method would you recommend: (i) the Naïve method, (ii) the Average method, or (iii) the Simple exponential smoothing method (assuming alpha= 0.8 and initial state (in December) of 8.5)?
Hi, I need help with solving for the following values (boxed). Thank you.
If month one has 240,000 demands, month two 250,080 demands, month three 325,00 demands, month four 370,000 demands, month five 420,000 demands and month six 509,00 demands. Use a forecast for the first month of 240,000, an initial trend forecast of 50,000, and smoothing parameters of 0.35 for both demand smoothing and trend smoothing. Compute the forecasts and trends using double exponential smoothing
Develop two exponential smoothing forecasts for periods 2 through 11. For the first forecast, use a=0.1. For the second, use a=0.7. Assume that your forecast for period 1 was 205. Click the icon to view the time series data. Find the exponential smoothing forecast for each period when a=0:1 (enter your responses rounded to one decimal place). Period Forecast (0.1) 205 1 2 More Info Period 1 2 3 4 5 6 7 8 9 10 Print Demand 228 249 229 238 231 154 166 157 Demand 228 249 164 161 Done
In a retail store, the actual sales of a particular product (in thousands of units) over the past few months are as follows: Month Sales 1 16 2 22 3 18 4 20 5 23 Using exponential smoothing method with α (smoothing constant) of 0.75 and the given forecast for month 1 equal to 10, what is the forecast for month 6?
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Use the following information to compute a single exponential smoothing model forecast with a smoothing constant (α = 0.30) to produce the actual demand for the period.) Use 115 as the initial forecast. Click the icon to view the demand for the previous 9 periods. Fill-in the table below for a single exponential smoothing forecast (enter your responses rounded to one decimal place). Period F(SES) 1 2 3 4 5 6 7 8 9 The forecast for period 10 is Period 1 115 117 182 23456789 133 107 96 177 176 (Enter your response rounded to one decimal place.) 144 U at 115 117 182 133 107 96 177 176 144 forecast for period 10. (Note: a, is
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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 Value 18 13 (a) Construct a time series plot. 20T 18 16- 14- Time Series Value O Week 1 2 3 4 5 6 What type of pattern exists in the data? O The data appear to follow a cyclical pattern. O The data appear to follow a trend pattern. 8 6 O The data appear to follow a seasonal pattern. O The data appear to follow a horizontal pattern. Week 1 2 0 1 3 4 5 6 18 13 15 12 (b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Time Series Value 16 14 18 + 2 13 15 4 5 6 15 12 16 3 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? 12 16 4 14 Week (c) Use a = 0.2 to compute the exponential smoothing values for the time series. Time Series Value 5 14 Forecast 6 Forecast 7 20 18 16 14 12 WE 10 2 + 7 @o 20 18 0 1 2 3 4 Week 5 6 00 0 1 2 3 4 5 Week 6 7…
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