point moving average method for the forthcoming penod
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- The data shown are quarterly revenues (in Sthousands) from Roget's Books from 2013-Q1 through 2020-Q2. 6. Quarter 2013-1 2013-2 2013-3 2013-4 2014-1 2014-2 2014-3 2014-4 2015-1 2015-2 2015-3 2015-4 2016-1 2016-2 2016-3 2016-4 2017-1 2017-2 2017-3 2017-4 Revenue 2372 2740 2518 4708 2392 Quarter 2018-1 2018-2 2018-3 2018-4 2019-1 2019-2 2019-3 2019-4 2020-1 2020-2 Revenue 2725 2924 3118 5112 2777 2949 1:27:04 2811 2685 4795 2812 2893 2848 4894 2687 2903 2674 4871 2844 2933 3237 5350 3035 3028 2791 5252 Click here for the Excel Data File, Data file should open in a new browswer window. Select "File" then "Save As" to download the file to your computer and be able to use it in Excel. a. Determine the regression equation. Regression equation: ŷ = | (Round to 1 decimal places.) b. Determine the specific index for each quarter places.) dexes should be in decimal form (e.g. 1.36 not 136). Rounded to 2 decimal Quarter Quarterly Index Q1 Q2 Q3 Q4 c. What are the estimated sales (forecast) for…(4) The Great Northwest Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the holiday season and during the spring. It has accumulated the following data for orders per season (quarter) during the past five years. Orders (1,000s) Year 1 Year 2 Year 3 Year 4 Year 5 Winter (Q 1) Spring (Q 2) Summer (Q 3) 18.6 18.1 22.4 23.2 24.5 23.5 24.7 28.8 27.6 31.0 20.4 19.5 21.0 24.4 23.7 Fall (Q 4) Total 41.9 46.3 45.5 47.1 52.8 104.4 108.6 117.7 122.3 132.0 Develop a seasonally adjusted forecast model for these order data. Forecast demand for each quarter for year 6, using the annual trend line as given: Y(t) = 96.33 + 6.89t (a) Find seasonal index for each quarter (b) Find seasonally adjusted demand forecast for each quarter for year 6 (c) Find MAD for seasonally adjusted forecasting for year 1 through 5.1 Given the data below. Find the forecast value from June to December Month Actual Demand Forecast January February 380 420 March 375 April May 285 325 June July August Sept October November December ?? ?? ?? ?? ?? ?? ??
- gnment 1.d X ment%202.pdf .xlsx HP Work & Supply Chain Marakane Sales JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Total - 1 / 2 - Question 1 The monthly demand of a company is showed below, please use the static method to forecast the demand for Year 6. Year 1 Q Search 2,000 3,000 3,000 3,000 4,000 6,000 7,000 6,000 10,000 12,000 14,000 8,000 78,000 Catherine Caramp....pdf Z Year 2 140% 3,000 4,000 3,000 5,000 5,000 8,000 3,000 8,000 12,000 12,000 16,000 10,000 89,000 LDE + @ I Assignment 2 Year 3 Question 2 Historical demand for Peeps is as displayed in the table. 2,000 5,000 5,000 3,000 4,000 6,000 7,000 10,000 15,000 15,000 18,000 8,000 98,000 T2202- 2022.pdf 0 Year 4 }}) 5,000 4,000 4,000 2,000 5,000 7,000 10,000 14,000 16,000 16,000 20,000 12,000 115,000 ! Year 5 5,000 2,000 3,000 2,000 7,000 6,000 8,000 10,000 20,000 20,000 22,000 8,000 113,000 Q☆ l EN USThe K&R Camera shop sells all the latest cameras and accessories. To meet customer demand, the manager must forecast demand for items she sells. Lately the XR-42S zoom lens has been very popular. Recent monthly demand for this item has been as shown: Number of Lenses Month Sold 1 12 17 2 3 4 15 20 18 23 6.The monthly demand for units manufactured by the Acme Rocket Company has been as follows:Month Units Month UnitsMay 100 September 105June 80 October 110July 110 November 125August 115 December 120a. Use the exponential smoothing method to forecast the number of units for June to January. Theinitial forecast for May was 105 units; a = 0.2.b. Calculate the absolute percentage error for each month from June through December and theMAD and MAPE of forecast error as of the end of December.c. Calculate the tracking signal as of the end of December. What can you say about the performanceof your forecasting method?
- 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 falnFind the MAD and Tracking signal in below table. Do you think this forecast is acceptable? Why? How many units this company shall keep as the safety stocks if service level is 90%? Period Actual Demand Forecast 220 200 2 300 310 3 400 340 4 340 350 5 280 300 250 270Determine the Forecast Error for the data below using the Mean Absolute Deviation (MAD) formula. Month Demand Forecast 16 205 210 17 197 175 18 230 210 19 240 228 20 252 220 Question 11 options: a) 15.8 b) 15.7 c) 19.1 d) 16.7
- Pls solve both for good ratingThe following table shows the three-period moving average and five-period moving average for monthly sales of Budget Furniture's during 2019. Moving averages of Budget Furniture's Time period Months Sales Three-period moving average (rounded off to Five-period moving average four decimals) R'millions 1 Jan 7 5.0000 6.2 February 5.6667 6.6 March 5 7.0000 B 4 April 8.3333 8.2 May 7 9.3333 8.4 June 8.3333 9.6 7 July 12 8.6667 9.6 August 4 A 9.2 September 10 10.6667 10 October 13 10.6667 11 November 9 12 December 10 The seasonal index for the month of February in 2019 is: LOTucson Machinery, Inc., manufactures numerically controlled machines, which sell for an average price of $0.5 million each. Sales for these NCMS for the past two years were as follows: Use Exhibit 18.10. LAST YEAR QUANTITY QUARTER (UNITS) THIS YEAR QUANTITY QUARTER (UNITS) 15 15 II III 21 II 27 31 29 19 III IV IV 15 a. Find the equation of a simple linear regression line using Excel. (Round your answers to 3 decimal places.)