The year has concluded and Sandy is evaluating the accuracy of her forecast. What is her Mean Absolute Deviation. Season Spring Summer Fall Winter 46.25 732.5 41.25 01 Forecast 275 1850 110 530 None of these are correct. Actual Sales 300 1900 100 630
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- Under what conditions might a firm use multiple forecasting methods?QUESTION 2:The manager of YTL Computers wants to develop next year’s quarterly forecasts of salesrevenue for its brand laptops. The sales are seasonal and the company believes that thefollowing most recent eight quarters of sales should be representative of next year’ssales: Year Quarter Sales (millions of dollars) 1 1 9.2 1 2 5.4 1 3 4.3 1 4 14.1 2 1 10.3 2 2 6.4 2 3 5.4 2 4 16.0 Determine the forecast of next year’s quarterly sales revenue for this line of laptops.Show all your workings.Question 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.
- Question 03 Suppose you sell stylish leather bags targeting young office going people who can use your bags to carry laptops and necessary stuff. You have already launched leather bags in February of this year and now based on the demand results of last 7 months, you want to predict the demand for your bags for the month of September. Hence, you want to select the right forecasting techniques and you are considering 2 period Moving Average, Naive technique and Exponential Smoothing (use any value between .10 - .15 as the value of alpha). Now figure out the better forecasting technique among 2 period Moving Average, Naive technique and Exponential Smoothing by doing the error calculation with the help of MAD, MSE, MAPE. Period Demand 2period Moving Average (Demand forecast) Naive technique (Demand forecast) Exponential Smoothing (Demand forecast) February 70 75 ** ** March 74 78 ** ** April 80 ** ** ** May 88 ** ** ** June…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.
- 2. The AirGo is the largest publicly listed low budget airlines company. On the negative side for the company, which spent billions of dollars in development costs, is the consistently negative cash flow due to poor prediction of its passengers. Question: Airlines company approaches you to suggest possible methods for an effective Forecast and it's Monitoring & Controlling. Help the airlines for the better prediction of its passengers.Q4 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 17Q1) Forecasting is both art and science. Describe the situations where we use Qualitative forecasting techniques and quantitative forecasting techniques
- New Accounts New Accounts Period 200 232 11 214 248 12 211 250 13 228 253 14 5 235 10 267 15 Using linear regression, what is your forecast for period 16? Less than 300 Between 301 and 308 Between 309 and 350 Period 1 2 3 4 O Higher than 350 Period 6 7 8 9 New Accounts 281 275 280 288 310Month 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.)q10- What is the best description of Granger-causality? Select one: a. the ability of lags of one variable to contribute to the forecast of another variable b. the ability of a variable to predict its own future c. the ability of the one variable to explain it own past d. None of the above Clear my choice
