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- Under what conditions might a firm use multiple forecasting methods?Q1) Forecasting is both art and science. Describe the situations where we use Qualitative forecasting techniques and quantitative forecasting techniquesQ4 ABC University wants to develop forecasts for next year's quarterly enrollment. It has collected quarterly enrollments for the past two years. It has also forecast total annual enrollment for next year to be 95,000 students. What is the forecast for each quarter of next year? Enrollment (in 000') Quarter Year 1 Year 2 Fall 24 25 Winter 23 22 Spring 18 19 Summer 15 17
- Q3) Discuss Qualitative forecasting technique. Explain the situations where we use Qualitative methods. Discuss Delphi forecasting method and its challenge.Given November actual demand of 61, November forecast of 58, and an alpha of 0.4, November trend value +1.03, Beta of 0.3 what would the forecast including trend (FIT) for the December period be using exponential smoothing model 2? Select one: a. 62.03 b. cannot be found c. 68.76 d. 65.72Question 1 ) The monthiy sales Of yamizí Battery company are asfollows:- Month Jales 2000 2100 1500 1400 1300 Calcuiate fore cost sales for June using each of the fo llowing method: - i) Naive Method 1M 3 Month Simple moving averoger Ti) Exponentral smoothing using an a =0:3 cand may forecast of 1600 units.
- QUESTIONS: Quarterly demand for a washing machine is as shown. 1. After obtaining initial estimates for level, trend, and seasonal factors. forecast the demand for the first quarter of year III using Winter's model with a 6- - 0,25 where x is the last two digits of your student number. 2. Make a tracking signal analysis for the forecast and evaluate Maks Year I II Quarter 1 2 3 4 1 2 3 4 Demand 1900 1224 4000 5600 4800 1048 6200 8000q1(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.6. Consider the following data table. (12 Points) a) Forecast demand using exponential smoothing with an apha of 0.25, and an initial forecast of 128.0 for period 1. b) Calculate the MAD and MSE. Period Real demand 130 138 129 140 3 4 5 133
- Month Demand Forecast Error Abs Error alpha 1 20 2 18 3 21 4 25 5 24 6 27 7 22 8 30 9 23 10 20 11 29 12 22 Mean Bias MAD (mean error) Problem 6: Maverick Jeans' demand manager decided to evaluate exponential smoothing. To maintain com- parability, she used the data from problem 6, copied below. 1 Month 2 3 Demand 20 18 21 25 4 5 24 6 7 8 9 10 11 12 27 22 30 23 20 29 22 Develop forecasts for months 5-12. Calculate the Bias and MAD. Use a starting forecast of 20 for month 4 and an alpha value of 0.2. (Note: Adjust all cell values to two decimal points.)1. Solve manually. The following gives the number of pints of type A blood used at Woodlawn Hospital in the past 6 weeks. Pints Used 360 Week August 31 September 7 September 14 September 21 September 28 389 410 381 368 October 5 374 a. Forecast the demand for the week of October 12 using a 3-week moving average. b. Use a 3-week weighted moving average, with weights of 0.1, 0.3 and 0.6, using 0.6 for the most recent week. Forecast demand for the week of October 12. c. Compute the forecast for the week of October 12 using exponential smoothing with a forecast for August 31 of 360 and c=0.2. d. Compute the MAD for the 3-week moving average, 3-week weighted moving average and exponential smoothing models above.Specific motors produces electronic motors for power-actuated valves for the Medicalconstruction industry. Specific's production plant has operated at near capacity forover a year now. JOSEPH Bakkabulindi, the plant manager thinks that the growth insales will continue, and he wants to develop a long- range forecast to be used to planfacility requirements for the next 3 years. Sales records for the past 10 years havebeen accumulated: N.B: Show all the workings. Solve with Linear regression. Year Annual sales (000's of units) Year Annual sales (000's of units 1 500 6 1,000 2 650 7 1,100 3 900 8 1,300 4 1,000 9 1,450 5 1,000 10 1,600
