A firm uses simple exponential smoothing with trend adjustment to forecast demand, "a = 0.6" and "B=0.6". The Forecast including Trend (FIT) for the 1st month of 2022 was 434 units whereas the actual demand turned out to be 488 units, the trend over that period was 26. Calculate the demand forecast including trend for the 2nd month.
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- 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_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_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?The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?Given the following history, use a three-quarter moving average to forecast the demandfor the third quarter of this year. Note that the 1st quarter is Jan, Feb, and Mar; 2ndquarter Apr, May, Jun; 3rd quarter Jul, Aug, Sep; and 4th quarter Oct, Nov, JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DECLast year 120 140 145 195 205 220 165 155 145 220 245 265This year 140 145 200 210 240 255
- 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.b. Kim’s department at a local department store has tracked the sales of a product over thelast nine weeks. The demand can be seen in the table below.Period Demand1 242 233 264 365 266 307 328 269 25i. Forecast demand using exponential smoothing with an alpha of 0.3, and an initialforecast of 30.0 for period 2 to 9.ii. Use a 5-period moving average, forecast the demand up to period 9.iii. Using MAD, determine which forecasting technique is better.Please do not give solution in image format thanku supose that the demand in period 1 was 7 units and the demand in period 2 was 9units . Assume that the forecast for period 1 was for 5 units .If the firm uses exponential smoothing with an alpha value of .20. what should be the forecast for period 3
- 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.Given the following history, use a three-quarter moving average to forecast the demand for the third quarter of this year. Note that the 1st quarter is Jan, Feb, and Mar; 2nd quarter Apr, May, Jun; 3rd quarter Jul, Aug, Sep; and 4th quarter Oct, Nov, Dec. (Round final answer to a whole number.) JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Last year 165 185 200 230 240 265 210 200 195 265 290 315 This year 175 200 165 260 260 200 Forecast for the third quarterBradley'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 a = 0.4. Forecast the number of calls for week 6, which is next week. Week Actual Service Calls 26 2 34 38 4 27 5 35 The forecast for week 6 is service calls. (Enter your response rounded to two decimal places.)