A company recorded monthly actual demand and the forecast for its product over the past five months. Compute MAD for October. [Select the appropriate range in which your answer falls.]
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![Question 30-
A company recorded monthly actual demand and the forecast for its product over
the past five months. Compute MAD for October. [Select the appropriate range in
which your answer falls.]
Month
Actual
Demand
June
July
August
September 24
October 26
20
23.
21
Forecast
18
22
23
24
27
More than 0 but less than or equal to 1.25
More than 1.25 but less than or equal to 1.50
More than 1.50 but less than or equal to 2.0
More than 2.0 but less than or equal to 2.25
More than 2.25](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F8dd879b8-7c6d-4dc9-82e9-7a59a17ae229%2F8885feb7-865b-48a8-bb9e-5391f3b834f7%2Fq1lvp3o_processed.jpeg&w=3840&q=75)
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- 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.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?
- 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 30q1(a)Imagine that you need to introduce a new gadget such as the Apple Watch. Determine which forecasting method is appropriate for projecting the future demand of such this gadget. b)ARIMA is mostly used to forecast future values using historical time series data, as we all know. Its primary use is in short-term forecasting with at least 38-40 historical data points and a small number of outliers. If we don't have at least 38 data points, we should consider using another strategy.formula refers Naive Forecast method. O a. Forecast value for the current period = Last period actual value O b. Last period forecast demand value = Actual value for the current period O c. Ratio of Actual value / Forecast value O d. Sum of all data / number of data
- Given the demand data, answer the following questions below. Year Sales 1 - 123 2 - 118 3 - 109 4 - 112 5 -100 6 -110 7 -124 8 - ? What will be the forecast demand in Year 8 using Naïve method?a.) 120b.) 110c.) 115d.) 124ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using the naive approach.The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER SALES 154 190 154 145 216 236 208 175 Use time series decomposition to forecast quarterly sales for the next year. (Do not round intermediate calculations. Round your answers to the nearest whole number.) Quarter Forecest 19 10 11 12
- The Fitter Snacker company sold 6,435 cases of snack bars in June of the previous year. They are expecting sales to increase by 3% this year. In addition, they are launching a promotional campaign in May, which they expect will increase sales in June by an additional 500 cases. April May Sales forecasting Previous year (cases) Promotion sales (cases) Previous year base (cases) Growth: Base projection (cases) Promotion (cases) Sales forecast (cases) June 6735 300 6435 193 6628 500 7128 Jan. Feb. March 5734 5823 5884 6134 6587 300 5734 5823 5884 6134 184 6287 189 3.0% 172 5906 175 177 6061 5998 6318 6476 5906 5998 6061 6318 6476 Calculate the sales forecast for June of this year that Fitter Snacker should use? Show all your calculation steps.constants of .6 and .9, develop fo recasts for the sales of VWBeetles. What effect did the smoothing constant have on the forecast?Use MAD to deternline which of the three smoothing constants (.3,.6, or .9) gives the most accurate forecast. ~ (MyLab OperationsManagement also includes a shorter (brief) version of this problem.)The following table shows the three-period moving average and five-period moving average for monthly sales of Budget Furniture's during 2019. Moving averages of Budget Furniture's Time period Months Sales Three-period moving average (rounded off to Five-period moving average four decimals) R'millions 1 Jan 7 5.0000 6.2 February 5.6667 6.6 March 5 7.0000 B 4 April 8.3333 8.2 May 7 9.3333 8.4 June 8.3333 9.6 7 July 12 8.6667 9.6 August 4 A 9.2 September 10 10.6667 10 October 13 10.6667 11 November 9 12 December 10 The seasonal index for the month of February in 2019 is: LO
