Problem 3-2 (Algo)National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as folMonthFeb.Mar.Apr.May.Jun.Jul.Aug.Sales(000) Units19228127224192722Click here for the Excel Data Filea. Forecast September sales volume using each of the following:(1) The naive approach.

The monthly sales for 7 months is given below:

National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as foll Month Feb. Mar. Apr. May. Jun. Jul. Aug. Sales (000) Units 19 22 8 24 19 27 22 Click here for the Excel Data File a. Forecast September sales volume using each of the following: (1) The naive approach. ***

National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as foll Month Feb. Mar. Apr. May. Jun. Jul. Aug. Sales (000) Units 19 22 8 24 19 27 22 Click here for the Excel Data File a. Forecast September sales volume using each of the following: (1) The naive approach. ***

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.6: Moving Averages Models

Problem 22P: The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six...

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The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
Under what conditions might a firm use multiple forecasting methods?
The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?
Month Demand Sept. 78 Oct. 80 Nov. 77 Dec. 85 Jan. Based on the time series data presented above, do the forecasts using 2-month moving average (2-MA) and single exponential smoothing (SES) with a = 0.4, and answer the following questions: %3D (i) What is the mean absolute deviation (MAD) for 2-MA? (ii) What is the mean absolute deviation (MAD) for SES a = 0.4 ? (iii) Based on what you got, which method is more accurate?
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows: Month Sales(000)Units Feb. 15 Mar. 23 Apr. 12 May. 25 Jun. 19 Jul. 28 Aug. 26 Forecast September sales volume using each of the following: (1) A linear trend equation
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows: Month Feb. Sales (000)Units 16 Mar 18 Apr. 13 May. 20 Jun. 22 Jul. Aug. 23 28 Click here for the Excel Data File a. Forecast September sales volume using each of the following: (1) The naive approach. Naive approach thousands 13
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
Worked Problems (Show your calculations in order to get full credit) 1. Favors Distribution Company purchases small imported trinkets in bulk, packages them, and sells them to retail stores. They are conducting an inventory control study of all their items. The following data for the year 2006 are for one such item, which is not seasonal. [10 Points] | Month Sales Jan Feb Mar Apr May Jun Jul 19 11 14 17 12 14 16 Aug 15 a. Use trend projection to estimate the relationship between time and sales (state the trend line equation in this problem). b. Calculate forecasts for February 2007, April 2007, and February 2008
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(4) The Great Northwest Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the holiday season and during the spring. It has accumulated the following data for orders per season (quarter) during the past five years. Orders (1,000s) Year 1 Year 2 Year 3 Year 4 Year 5 Winter (Q 1) Spring (Q 2) Summer (Q 3) 18.6 18.1 22.4 23.2 24.5 23.5 24.7 28.8 27.6 31.0 20.4 19.5 21.0 24.4 23.7 Fall (Q 4) Total 41.9 46.3 45.5 47.1 52.8 104.4 108.6 117.7 122.3 132.0 Develop a seasonally adjusted forecast model for these order data. Forecast demand for each quarter for year 6, using the annual trend line as given: Y(t) = 96.33 + 6.89t (a) Find seasonal index for each quarter (b) Find seasonally adjusted demand forecast for each quarter for year 6 (c) Find MAD for seasonally adjusted forecasting for year 1 through 5.