The following table shows the quarterly sales (RM'000) for Afeef Café for the past 3 years. Quarter Year 1 2 3 4 2019 11 17 10 18 2020 2021 19 24 17 29 23 38 31 33 Based on the above data. (b) Calculate the seasonal indices using the multiplicative model.
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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.ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using a five-month moving average approach.ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using the naive approach.
- Asvnch 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.The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER SALES 1 215 2 240 3 205 4 190 5 160 6 195 7 150 8 140 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to 1 decimal place.Describe four (4) features common to all forecasts techniques.
- Please consider the following information and make forecasts for January, February, March, and April of Year 2. Use second-order polynomial regression to make forecasts. Adjusted seasonal index Actual sales Deseasonalized sales 836 825 Year 1 Year 2 January February March April May June July August September October November December January February March April 0.72 0.75 1:22 1.48 1 1.23 0.7 0.78 0.92 1.13 1.28 1.33 0.72 0.75 1.22 1.48 1220 1319 1020 1184 685 641 875 1008 1068 1141The following table shows the quarterly sales (RM'000) for Afeef Café for the past 3 years. Quarter Year 2 3 4 2019 11 17 10 18 2020 19 24 17 29 2021 23 38 31 33 Based on the above data. (c) Forecast the sales for the third quarter of 2022.B). Using exponential smoothing, calculate the forecasts for months 2, 3, 4, 5, and 6. The smoothing constant is 0.2, and the old forecast for month I is 245. Month Actual Demand Forecast Demand 1 260 2. 230 3 225 4 245 5 250 6. C). Given the following average demand for each month, calculate the seasonal indices for each month. Month Average Demand Seasonal Index January 30 February 50 March 85 April 110 May 125 June 245 July 255 August 135 September 100 October 90 November 50 December 30 Total 3 D). Using the data in part A and the seasonal indices you have calculated, calculate expected monthly demand if the annual forecast is 2000 units. Month Seasonal Forecast Index January February March April May June July August September October November December
- Given the following historical data, what is the moving-average forecast for period 6 based on the last three periods? Last Value Forecast? Period Value 1 73 2 68 3 65 4 72 5 67Font Paragraph Styles Question 3 Consider the following from an estate agent's business nationally: Month Houses Sold Jan Feb Mar 380 360 390 Apr May June July Aug Sep Oct 400 390 380 394 454 460 460 Nov Dec 430 370 a) Calculate the three point moving averages (quarters) and seasonal variation for the above data b) Define moving averages and how they're useful in forecasting (use Harvard referencing) c) At races, your horse, White Rum, has a probability of 1/20 of coming 1st, 1/10 of coming 2nd and a probability of 4 in coming 3rd. First place pays $5,000 to the winner, second place $4,000 and third place $1,350. Hence, is it worth entering the race if it costs $1050?Explain 4 methods of time series in demand forecasting with an examples.
