Maria sells banana que every afternoon. She sells her product everyday except during Sundays. The number of pieces sold last week were 57, 43, 37, 40, 55, and 47, respectively. Although actual sales are given, compute for the forecasted quantity using the following forecasting techniques: 1. Naïve; 2. 2-day moving average; and
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- Under what conditions might a firm use multiple forecasting methods?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 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 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?Pumpkin Pies Galore is trying to forecast sales of pies forthe month of December. Demand for pies in September, October,and November has been 230, 304, and 415, respectively. Edith, thecompany’s owner, uses a three-period weighted moving averageto forecast sales. Based on her experience, she chooses to weightSeptember as 0.1, October as 0.3, and November as 0.6.(a) What would Edith’s forecast for December be?(b) What would her forecast be using the naïve method?(c) If actual sales for December turned out to be 420 pies,which method was better (use MAD)?12-1. The Hartley-Davis motorcycle dealer in the Minneapolis- St. Paul area wants to be able to forecast accurately the de- mand for the Roadhog Super motorcycle during the next month. From sales records, the dealer has accumulated the data in the following table for the past year. Month January February March April Мay June Motorcycle Sales 7 10 8 7 12 July August September 10 11 12 October 10 November December 14 16 a Compute a three-month moving average forecast of demand for April through January (of the next year). b. Compore a five-month moving average forecast for June drough January. c. Compare the two forecasts computed in parts (a) and (b) using MAD. Which one should the dealer use for January of dhe next year?
- A manager uses a trend equation plus quarterly relatives to predict demand. Quarter relatives areSR1 = .90, SR2 = .95, SR3 = 1.05, and SR4 = 1.10. The trend equation is: Ft= 10 + 5t. Over thepast nine quarters, demand has been as follows:Period, t 1 2 3 4 5 6 7 8 9Demand 14 20 24 31 31 37 43 48 52Is the forecast performing adequately? Explain.4. A local moving company has collected data on the number of moves they have been asked to perform over the past two years. Moving is highly seasonal, so the owner/operator, who is both burly and highly educated, decides to apply the multiplicative seasonal method to forecast the number of customers for the coming year. The equation for the trend line of yearly sales is F1 = 100 + 60t. Please forecast demand for each quarter in Year 3. (Round the forecasts to whole numbers and show all calculations t Complete the table below and forecast the sales of Year 3 by quarter. Copy the table below, paste to the answer box and fill in your answers. You need to take a picture of your work and upload the picture in next question. Year 1 Year 2 Year 3 Quarter Demand Quarter Demand Quarter Demand 1 28 1 45 1 43 60 2 120 140 4 49 55 4 Total 240 Total 300 Total Average Average Average For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac).1. Which of the following is indicative of the season of heaviest demand when seasonality is measured on a quarterly basis? a. Seasonal index = .75 b. Seasonal index = 1.0 c. Seasonal index = 1.25 d. Seasonal index = 3.1 Answer: 2. The forecast calculated at the end of period t for period t+k is always the same for any value of k if the time series has systematic variability. A) True B) False
- 1. Forecasting stationary series The company Handy Inc. produces a solar-powered electronic calculator that has experienced the following monthly sales history for the first four months of the year (in thousands of units): January February. March. April sales 23.3. 72.3. 30,3. 15.5 a) Find the forecast for May using the Moving Averages method with N = 3. b) Assume that the forecast for January was 25. Determine the one-step ahead forecast for February through May, using exponential smoothing with a smoothing constant of α = 0.15. c) Repeatthecalculationinproblembforavalueofα=0.40. d) Compare the MAD (Mean Absolute Deviation) and MSE (Mean Squared Error) for the forecast for February to April in problems b and c. Comment the accuracy of the forecasts. e) The demand in May turned out to be 30. Which of the three forecasting method were most accurate for this prediction? 2. Regression analysis 3 000 000 2 500 000 2 000…The demand (in number of units) for Apple iPad over the past 6 months at BestBuy is summarized below. Month Nov 2019 Dec 2019 Demand 45 48 Jan 2020 50 Feb 2020 Mar 2020 Apr 2020 42 46 51 Consider the following three forecasting methods: • Two-month weighted moving average, with weights 6 and 2 (more weight assigned to more recent data) Exponential smoothing with a = 0.7. Let the initial forecast for Nov 2019 be 46. • A trend line projection in the form ŷ = a+bx . To simplify computations, transform the value of x (time) to simpler numbers – designate Nov 2019 as x=1, Dec 2019 as x= 2, etc. (a ) For each of the above methods, forecast the demand of Apple iPad for May 2020. (b) Consider only the two-month weighted moving average method, compute the MAD measure and the MSE measure using the data from Jan 2020. (c) Use the trend line to forecast the demand of Apple iPad for Dec 2020. Give your opinion regarding the reliability of the forecast.Forecast sales for the 7th period. For leveling, use exponential smoothing 0.20 and moving average 3 for averaging; and linear and exponential functions for trend data. Assume an initial exponential forecast of 60 units in period 2 if you decide to use it (i.e., no forecast for period 1). Period Demand 1 67 2 72 3 68 4 20 5 70 6 66 7 68
