a. b. C. d. Calculate simple average for the entire sales. Calculate 3-months moving average. Calculate 3-months centered moving average Calculate sales forecast for the month of July.
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- Under what conditions might a firm use multiple forecasting methods?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 8000Question 1 Q1) The monthly sales of a retailer company were as follow: Month -Sales February-- March- 1000 1800 April- -2100 May- -1000 June- July-- 2048 2600 August As a planner, you are required to calculate the Demand Forecast for August using the Naive approach Add your answer
- 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.Part C Exponential Exponential Gasoline Demand Gasoline Month smoothed forecast smoothed forecast Exponential smoothed forecast (a = 0.25) Demand (a = 0.25) (a = 0.45) Exponential smoothed forecast (a = 0.45) Mar 900 920 920 1200 Apr May 755 915.00 911.00 1100 1000 650 875.00 840.80 g20 915.00 846 80 755 818.75 754.94 904.76 835.12 Jun 550 818.75 754.94 800 320 751.56 66272 645.74 746.83 Jul 625 751.56 662.72 650 600 550 Aug Sep 730 719.92 645.74 820 722.44 683.66 400 D Oct 1100 746.83 745.01 200 1 Nov 835.12 904.76 Mar Apr May Jun Jul Aug Sep Oct Nov 1. Make a comparative analysis out of your answers in the plotted data. (3-5 5 sentences)Al Maha Plastic manufacturing Companies last Six weekly values of Sales were 90, 110, 115, 135, 140, 150 and 160 units. Forecasts (same for all the six weeks) were 110 units for all the weeks. Calculate MAD, and Tracking Signal for these six weeks. Wee k Actual Sales Forecaste d Sale Error Cumulative Error Absolute Error Cumulative Absolute Error MAD Tracking Signal 1 2 3 4 5 6 7
- Question content area Part 1 Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Year Sales 1 450 2 510 3 516 4 555 5 575 Part 2 a) Forecasted sales for year 6 using the trend projection (linear regression) method are enter your response here sales (round your response to one decimal place). Part 3 b) The MAD for a linear regression forecast is enter your response here sales (round your response to one decimal place). Part 4 c) The MSE for the linear regression forecast is enter your response here sales (round your response to one decimal place).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.Month Actual Sales Naive Forecast- Absolute Value of (# of Product X) Sales Errors (# of Product X) Jan/19 Feb/19 Mar/19 Apr/19 May/19 Jun/19 Jul/19 Aug/19 Sep/19 Oct/19 Nov/19 Dec/19 Jan/20 1,860 2,033 3,556 4,211 6,250 7,990 10,250 9,850 9,980 9,990 7,895 5,353 - Explain the calculation method for the Naive Forecast model. the faln
- QUESTION 8 You are given the following information, comprising of an individual's expenses for the year 2015. Use the information provided hereunder to answer the following questions. Month January February March April May June July August September October November December Expenses 1977 820 970 1082 1220 1281 1546 1788 895 1108 1824 1954 a) Determine the expenses forecast using a two (2) period moving average. Calculate the MAD and MSE. b) Determine the expenses forecast using a two (2) period weighted moving average. Use 0.8 & 0.2 for the weights of the most recent and second most recent periods respectfully. Calculate the MAD and MSE. c) Develop an exponential smoothing forecast using a=0.2. Assume the forecast for the first month is the actual expenses for that month. Calculate the MAD and MSE. d) Developed a trend line to forecast expensesq1(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.b. Given the demand and forecast values shown in the following Table Q3b, i.Determine the three-period moving average forecast for November. ii. Analyze the exponential smoothing forecast for November using a = 0.35. iii. Evaluate the forecast error for September.
