esProblem 3-21 (Algo)Two different forecasting techniques (F1 and F2) wereused to forecast demand for cases of bottled water. Actualdemand and the two sets of forecasts are as follows:Period Demand1234567875PREDICTED DEMANDF264627068 万 70 74 69 2 80 78343772F16266716767773122806073767979 results, which forecast appears to be more accurate?(Round your answers to 2 decimal places.)F1MSE F1MSE F2appears to be more accurate.Check my workc. In practice, either MAD or MSE would be employed tocompute forecast errors. What factors might lead amanager to choose one rather than the other?Either one might already be in use, familiar to users, and have past values for comparison. If conMAPE F1MAPE F2d. Compute MAPE for each data set. Which forecastappears to be more accurate? (Round your intermediatecalculations to 2 decimal places and and final answers to2 decimal places.)%%

Actual demand for 8 periods along with 2 different forecasts are provided below:

Answered: Two different forecasting techniques…

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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Below is a table containing data on product demand for the most recent five months along with the forecasts that had been made for those 5 previous months. Use the 3-period simple moving average method to forecast the number of sales to expect next month. Month Demand Forecast 1 308 341 388 343.3 3 344 364.7 4 400 346.7 341 377.3
Two different forecasting models were used to forecastsales of a popular soda on a college campus. Actual demand andthe two sets of forecasts are shown. Use MAD to explain whichmethod provided a better forecast.
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A Use a simple moving average model. Experiment with the models using five weeks and three weeks past data. 3 week MA Week ATL BOS CHI DAL LA TOTAL 1 2 3 4 5 6 7 8 9 10 11 12 13 5 week MA Week ATL BOS CHI DAL LA TOTAL 1 2 3 4 5 6 7 8 9 10 11 12 13 B evaluate the forecast that would have been made over the 13 weeks using overall mean absolutely deviation, mean absolute percent error, and tracking signal as criteria.
National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below: Sales (1000 units) Forecast Observation Month Yt Ft 1 February 19 2 March 18 3 April 15 4 May 20 5 June 18 6 July 22 7 August 20 8 September ? Use Excel to plot the data and forecast September sales using the following methods: The naïve forecast A three-month moving average Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19 A 3-month weighted moving average, with weights 0.60, 0.3, and 0.1. With 0.6 applied to the most recent past.
4. An electrical contractor's records during the last five weeks indicate the number of job requests: 1 3 20 18 Week Requests 2 22 4 21 5 22 Predict the number of requests for week 6 using each of these methods: a. Naive b. A four-period moving average c. Exponential smoothing with a = 30; use 20 for week 2 forecast
4. The sales (in millions of dollars) for an 18-month period are as follows. Month Sales Month Sales 1 600 600 775 10 775 3 600 11 600 4 650 12 575 700 13 625 800 14 650 550 15 600 8 775 a. Compare a three-month moving average forecast with an exponential smoothing forecast. Use a = 0.1. Which provides the better forecasts based on MSE? b. Find the forecast for the next month using the best forecast method. 2.
Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows:
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using minitab
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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Two different forecasting techniques (F1 and F2) were used to forecast demand for cases of bottled water. Actual demand and the two sets of forecasts are as follows: Period 1 2 3 4 5 678 Demand 68 75 70 74 69 72 80 78 PREDICTED DEMAND F2 64 62 70 73 76 79 79 80 F1 62 66 71 67 73 67 73 77