(a) Compute the forecast sale using a = 0.20 and a = 0.35 respectively, (b) solve for MAD, SSE, MSE, and MSE (c) Forecast the next month's (May-19) sale, and (d) which forecast value is better to use in terms of MSE, explain why? (Note: express all answers using 4 decimal places) %3D
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(Note: express all answers using 4 decimal places)
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- 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 USDFC Company has recorded the past years sales for the company: Year(t) Sales(x) (in Million Pesos) 2011(1) 2012(2) 2013(3) 2014(4) 2015(5) 2016(6) 2017(7) 2018(8) 2019(9) 2020(10) 219 224 268 272 253 284 254 278 282 298 Use the naïve model. Compute for MAE and MSE Use a three period moving average. Compute for the MAE and MSE Use the simple exponential smoothing to make a forecasting table. Compute the MAE and MSE of the forecasts. Alpha = 0.1 Use the least square method to make the forecasting table. Compute the MAE and MSE *** Use excel or r programmingyear quarterly sales (000 units) Q1 Q2 Q3 Q4 2016 1300 1500 1200 2000 2017 1600 1800 1100 2200 2018 1700 1900 1300 2300 2019 1800 2100 1400 2500 Using a simple regression analysis, determine the trend equation of the sales and use it to estimate the number of units of clothing sold throughout the fiscal year 2020. Assume that Q1 of 2016 is 1, Q2 of 2016 is 2, etc. Show all relevant cakculation detail
- The 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: LOFrom the following time series data of sale project the sales for the next three years. Year 2001 2002 2003 2004 2005 2006 2007 Sales (*000 units) 80 90 92 83 94 99 92(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.
- Fill the following blanks with appropriate abbreviations supplied: ________ =mean absolute percentage error, ________ = fixed cost, _______ = slope, _______ = correlation coefficient, _______ = smoothing constant, ________ = intercept, _________ = trend smoothing constant, α FC β MAPE b r aForecast error is measured using the following formula. O a. Actual value = Forecast value O b. Forecast value = Actual value O C. Actual value - Forecast value o d. Forecast value - Actual valuePlease do not give solution in image formate thanku. Bradley's Copiers sells and repairs photocopy machines. The manager needs weekly forecasts of service calls so that he can schedule service personnel. Use the actual demand in the first period for the forecast for the first week so error measurement begins in the second week. The manager uses exponential smoothing with α = 0.5 Forecast the number of calls for week 6, which is next week. WEEK ACTUAL SERVICE CALLS 1 28 2 32 3 40 4 27 5 30
- 3. Quarterly sales of a car dealer exhibit an almost constant mean over time, but sales fluctuate depending on the quarter of the year (exhibits seasonality). Quarter Q1 - Spring Q2 - Summer Q3 - Fall Q4 - Winter Mean Year 1 32 74 53 22 45.25 Year 2 30 71 63 15 44.75 Year 3 35 83 45 19 45.5 (a) Using three years' worth of quarterly data that is provided, develop a set of seasonal factors that could be used to forecast car sales (b) Forecast car sales in each of the four quarters (Q1-Q4) of the following year (Year 4), using these seasonal factors.b. The mean absolute deviation as of the end of week 10 is___ rentals enter your response here. (Enter your response rounded to two decimal places.)1. The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Part 2 Week Of Pints Used August 31 350 September 7 372 September 14 412 September 21 381 September 28 366 October 5 378 Part 3 a) The forecasted demand for the week of October 12 using a 3-week moving average LOADING... = _____________pints (round your response to two decimal places).