A large Portland manufacturer wants to forecast demand for a piece of pollution-control equipment. A review of past sales ($A_t$), as shown below, indicates that an increasing trend is present. Smoothing constants are assigned the values of $\alpha = 0.20$ and $\beta = 0.4$. The firm assumes the initial forecast for month 1 ($F_1$) was 9.00 units and the trend over that period $T_4$ was 2.00 units.Using trend-adjusted exponential smoothing, Forecasts ($F_t$), Trend ($T_t$), and Forecasts Including Trend ($FIT_t$) for months 1 through 4 have already been developed and are provided below. Continue with the process and determine $F_t$, $T_t$, and $FIT_t$ for months 5 and 6 (round your responses to two decimal places):\[\begin{array}{|c|c|c|c|c|}\hline\text{Month (t)} & \text{Actual Demand (A_t)} & \text{Forecast (F_t)} & \text{Trend (T_t)} & \text{Forecast Including Trend (FIT_t)} \\\hline1 & 10.0 & 9.00 & 2.00 & 11.00 \\2 & 16.0 & 10.80 & 1.92 & 12.72 \\3 & 23.0 & 13.38 & 2.18 & 15.56 \\4 & 20.0 & 17.05 & 2.78 & 19.83 \\5 & 25.0 & - & - & - \\6 & 22.0 & - & - & - \\7 & 30.0 & - & - & - \\8 & 26.0 & - & - & - \\9 & 38.0 & - & - & - \\10 & - & - & - & - \\\hline\end{array}\]

A forecasting technique called "Trend-Adjusted Exponential Smoothing" is used to make predictions…

Answered: A large Portland manufacturer wants to…

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 monthly sales for Yazici Batteries, Inc., were as follows: Month Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Sales 21 20 15 12 15 16 15 17 19 21 20 24 Using a method of trend projection, the forecast for the next month (Jan) = ______ sales (round your response to two decimal places).
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.
Demand for oil changes at Garcia's Garage has been as follows: Number of Oil Changes January 44 February 49 March 66 IT April 59 May 53 June 58 59 63 Month July August a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For Janu The forecasting model is given by the equation Y=+x. (Enter your responses rounded to two decimal places) J Show Transcribed Text >. Use the model to forecast demand for September, October, and November. Here, X=9, 10, and 11, respectively. (Enter your responses rounded to two decimal places.) Forecast for the number of Oil Changes Show Transcribed Text Month September October November can you do all the parts please corrrect
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The following are monthly actual and forecast demand levels for May through December for units of a product manufactured by the Deborah Bishop Company in Des Moines: Month May June July August September October Actual Demand 105 82 110 112 108 106 130 120 Forecast Demand 100 108 97 98 108 102 105 107 November December For the given forecast, the tracking signal = MADS (round your response to two decimal places).
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: Year Year Forecast (000) 1 2 4.00 7.00 1 5.00 3 5.00 Registrations (000) a) Calculate the forecasted registrations for years 2 through 12 using exponential smoothing, with a smoothing constant (a) of 0.40 and a starting forecast of 5.00 for year 1 (round your responses to one decimal place): 2 3 4.6 5.56 4 4.00 4 5.34 11 9 10 7 8 6 5 9.00 9.00 6.00 10.00 13.00 14.00 12.00 5 4.80 6 7 6.48 7.49 8 6.89 9 8.14 10 10.08 11 11.64 12 11.79 b) Mean absolute deviation based on the forecast developed using the exponential smoothing method (with a smoothing constant (a) = 0.40 and a starting forecast of F₁ = 5.00) is response to one decimal place). registrations (round your
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Since the beginning of the year, the purchase manager at a department store has been recording sales data to be used to compute 4-period moving averages to forecast sales for an upcoming month. Sales data for the months of January through September are reported in the table below. Month January February March April May June July August September Sales 21 20 39 22 29 14 42 28 27 Computed forecast values are not rounded. Compute the four-period moving average forecast for October. value as a whole number by rounding. Specify the Compute the mean absolute deviation (MAD) for the four-period moving average forecasts. Specify the MAD as a whole number by rounding. Compute the mean squared error (MSE) for the four-period moving average forecasts. Specify the MSE as a whole number by rounding. Compute the mean absolute percentage error (MAPE) for the four-period moving average forecasts. Specify the MAPE as a whole number by rounding. CHECK ANSWER

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