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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?Week Sales1 27502 31003 32504 28005 29006 30507 33008 31009 295010 300011 320012 3150Develop a three-week moving average. A.What is the forecast for week 5? (Make sure no decimal place and no comma. EX: 1234) B.What is the value of MSE (mean squared error) with regard to a three-week moving average? (Make sure no decimal place and no comma. EX: 1234) C.Develop the exponential smoothing with the alpha value of 0.20. What is the forecast for week 5? (Make sure no decimal place and no comma. EX: 1234) D.What is the value of MSE (mean squared error) with regard to the exponential smoothing? (Make sure no decimal place and no comma. EX: 1234) E.Which method is more accurate? (1 for Moving average, 2 for Exponential Smoothing)
- The table shows the values found in the error analysis. What method of forecasting would be best to use? What is the forecasted value? MSE forecast for week 13 Time Series 1.08 14.76 3-week MA 3.04 13.67 exp smoothing 11.04 9.5 Group of answer choices A.) Time Series, forecasted value = 14.76 B.) 3-week MA, forecasted value = 13.67 C.) exp smoothing, forecasted value = 9.5 D.) Time Series, forecasted value = 1.08 E.) 3-week MA, forecasted value = 3.04 F.) exp smoothing, forecasted value = 11.04The following gives the number of pints of type Bblood used a t Woodlawn Hospital in the past 6 weeks: a) Forecast the dema nd for the week of October 12 using a3-week moving average.b) Use a 3-week weighted moving average, with weights of .I , .3,and .6, using .6 for the most recent week. Forecast demand forthe week of October 12.c) Compute the forecast for the week of October 12using exponentialsmoothing with a forecast for August 31 of 360 and a = .2Asvnch Problem - Statistical Forecasting Data Set – Eunice BC Fashion Monthly Sales, in million units. Year Total Sales Year Total Sales 2010 38 2016 43 2011 41 2017 40 2012 40 2018 45 2013 45 2019 47 2014 50 2020 42 2015 42 2021 48 Questions: a. Find the naïve forecast. b. Use the 3 years moving average forecast. c. Have a 5 years weighted moving average. d. Develop forecast using exponential smoothing with a = 0.2. e. Determine the trend line equation and present the forecast. f. Find the best forecast for year 2022. Note: Use the first 5 years as the training samples and the last 5 years as the forecasting samples. Solve it in Excel Sheet/Sheet with Equations as possible.
- 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?14.5. For the data in Exercise 14.4, use an a of 0.1 to make a forecast for July F Ft-1 + 0.1(At-1-Ft-1) Months January 15 February 18 March 22 23 27 26 April May June Demand Smoothing unit (At) (St) July 15 15.3 15.97 16.67 17.7 18.53 Forecast for July= 18.53 Forecast (Ft) 15 15.3 15.97 16.67 17.7 18.53Qualitative forecasting methods should be used only asa last resort. Agree or disagree? Comment.
- 1. Discuss the differences between Qualitative and Quantitative forecasting models. How do Associative and Time Series techniques differ? 2. What is the Mean Absolute Deviation (MAD)? 3. Use the following set of data to calculate the Mean Absolute Deviation (MAD) for the following set of data. Actual (A:) Forecast (Ft) Forecast Error Absolute (Deviation) Month Forecast Eror January February March 45 45 42 50 34 45 April 48 40 Мay 38 45 MAD =A forecasting method has produced the following over the past five months. What is the mean absolute percentage error (MAPE)? Actual 11 OA. 0.00% B. 31.87% 5178 11 13 Forecast 13 10 30668 $7Practice Problem: Usins the data on a hospital’s revenue: (1) Use simple exponential smoothing to make predictions for the hospital’s revenues during the next four quarters with α = 0.30. (2) Use Trend-Adjusted Exponential Smoothing(i.e. Holt’s method) to make forecasts for the hospital’s revenues during the next four quarters. Assume α = 0.05, β = 0.65, initial revenue forecast = 1209285.75 and initial trend forecast = 15714. (3) Using least-squares regression with seasonal index decomposing method, forecast the hospital’s revenues during the next four quarters.