i can email the excel spreadsheet that was provided with al the data. i dont know how to do that.

Question-2. Use the data in the Excel file provided to forecast the demand of a particular product using various methods and time periods as noted below. NOTE: YOU MUST SHOW ALL YOUR WORK IN THE EXCEL FILE. MAKE SURE YOUR ANSWERS APPEAR IN THE WORKSHEET THAT IS NAMED "TEMPLATE." YOU CAN CREATE NEW WORKSHEETS OR SHOW ADDITIONAL WORK IN THE WORKSHEET PROVIDED. a. Prepare a time-series plot of the data. Does the data appear to have a trend or seasonality? b. Use the naive method to forecast the demand for the last three months of 2016. c. Use the moving average method with 4 periods, i.e., MA(4), to forecast the monthly demand for January 2016 through December 2016. KSB 631 d. Use the exponential smoothing method with a=0.4 to forecast the monthly demand for January 2016 through December 2016. Use the actual demand observed in January 2015 as your initial forecast for January 2015 (That is, start the model in January 2015. e. Fit a trend line to the data provided for January 2015 to December 2015. Using the equation of the trend line you found, forecast the monthly demand for January 2016 through December 2016. f. Compute the MAD for each method, that is, the Nave, MA(4), ES(0.4), and the trend line during January 2016 to September 2016. g. Choose one of the time-series methods you analyzed thus far which will provide you the most reliable estimate and why? What are the demand forecasts for the last three months of 2016 if this method is used? 1 1560 19 2031 May 2037 2033 July 2004 August 2015 Septembe 2035 October 2017 November 2018 December 20 20 22 23 2M 20 2033 July 1530 21 2034 August 1620 22 2035 September 23 2036 October to be forecast 24 2037 November to be forecast 25 2038 December to be forecast 26 27 28 Year Month Demand Naive 29 2015 January 1560 30 2015 February 1680 1560 31 2015 March 1710 1550 32 2015 April 1740 1710 33 2015 May 1680 1740 34 2015 June 1752 35 2015 July 1680 36 2015 August 1560 37 2015 September 1650 38 2015 October 1800 39 2015 November 1860 40 2015 December 1800 Naive 41 2016 January 1530 1800 42 2016 February 1650 1530 43 2016 March 1620 1650 44 2016 April 1710 1620 45 2016 May 1680 1710 46 2016 June 1620 1680 47 2016 July 1530 1620 48 2016 August 1620 1530 49 2016 September 1560 1620 50 2016 October to be forecast 1560 51 2016 November to be forecast 1560 52 2016 December to be forecast 1550 53 54 55 Naive 56 MAD 93.3333333 57 58 59 Difference 0% ANAME? 0% 0% 0% 0% 0% 0% 0% O% Forecasts MA 1778 1748 1710 1650 1628 1665 1658 1535 1613 1583 1570 1590 Trendline Time Index Actual Observations 1 1560 2 1680 3 1710 4 1740 5 1680 6. 1752 7 1680 8 1560 9 1650 10 1800 11 1860 12 1800 13 1530 14 1650 15 1620 16 1710 17 1680 18 1620 19 1530 20 1620 21 1560 22 to be forecast 23 to be forecast to be forecast Naive Absolute Forecast for MA ES Trendline ES FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8888888 120 30 00 30 50 90 90 50 + Forecasts MA ES Trendline Student Name Forecasting Data and Template Ready . Calibri - 11-AAE BIU-- General Normal El Mergea Center - $ 969 Ciboard Font Forming Alignment be C D E F O Dema Time series plot Tras More 2015 January 2016 Februar Man 1680 1710 Actual Observations ISO 1710 8 9 y24 13 May + 2020 June Jul 1580 9 2002 70 2021 September Genober 1800 12 2005 November 2006 December 14 302 January 1530 15 7024 February 16 2020 March 152 77 200 April 1710 18 21 May 19 2020 June 1620 July 21 2034 August SOOD 22 2015 September 1560 21 2015 October to be forca 24 2037 November habe forca 25 2009 December to be forecast 26 M 2015 Lamar 2005 Feb 2012 March April 2009 May 2020 2021 2022 A 20173 pembe 2014 October 2005 November 2006 December 200 January 2001 2009 Math 20 Apr 2013 My 2012 July 2054 2055 pembe 2055 October 2017 November 2018 December 2 . 12 1 12 18 10 19 20 21 ISSO 1560 to before to be fout to be forecast Difference 1560 AME 29 2025 Lanuary 30 2015 February 51 2015 March 32 2015 113015 May 2015 June 1550 1660 1710 1740 10 1752 os 36 2015 August Professor, Inputed the correct rendline even though I can't get 1050 1800 1860 0% ON Time index cual Observations 1560 2 160 5 1710 1740 5 179 2 1680 1 1560 9 10 1800 11 1860 12 11 1530 14 16 16 36 1710 12 18 MA ES Trendine Trendline 2015 October 2015 November 20 2015 December 41 2016 January 42 2016 February 41 2016 March 44 2016 45 2016 May Na 270 130 FALL 1650 10.30 1650 R&RS 30 90 30 16BD Student Name AL 34 Forecasting Data and Template c CA Question-2. Use the data in the Excel file provided to forecast the demand of a particular product using various methods and time periods as noted below. NOTE: YOU MUST SHOW ALL YOUR WORK IN THE EXCEL FILE. MAKE SURE YOUR ANSWERS APPEAR IN THE WORKSHEET THAT IS NAMED "TEMPLATE." YOU CAN CREATE NEW WORKSHEETS OR SHOW ADDITIONAL WORK IN THE WORKSHEET PROVIDED. a. Prepare a time-series plot of the data. Does the data appear to have a trend or seasonality? b. Use the naive method to forecast the demand for the last three months of 2016. c. Use the moving average method with 4 periods, i.e., MA(4), to forecast the monthly demand for January 2016 through December 2016. KSB 631 d. Use the exponential smoothing method with a=0.4 to forecast the monthly demand for January 2016 through December 2016. Use the actual demand observed in January 2015 as your initial forecast for January 2015 (That is, start the model in January 2015. e. Fit a trend line to the data provided for January 2015 to December 2015. Using the equation of the trend line you found, forecast the monthly demand for January 2016 through December 2016. f. Compute the MAD for each method, that is, the Nave, MA(4), ES(0.4), and the trend line during January 2016 to September 2016. g. Choose one of the time-series methods you analyzed thus far which will provide you the most reliable estimate and why? What are the demand forecasts for the last three months of 2016 if this method is used? 1 1560 19 2031 May 2037 2033 July 2004 August 2015 Septembe 2035 October 2017 November 2018 December 20 20 22 23 2M 20 2033 July 1530 21 2034 August 1620 22 2035 September 23 2036 October to be forecast 24 2037 November to be forecast 25 2038 December to be forecast 26 27 28 Year Month Demand Naive 29 2015 January 1560 30 2015 February 1680 1560 31 2015 March 1710 1550 32 2015 April 1740 1710 33 2015 May 1680 1740 34 2015 June 1752 35 2015 July 1680 36 2015 August 1560 37 2015 September 1650 38 2015 October 1800 39 2015 November 1860 40 2015 December 1800 Naive 41 2016 January 1530 1800 42 2016 February 1650 1530 43 2016 March 1620 1650 44 2016 April 1710 1620 45 2016 May 1680 1710 46 2016 June 1620 1680 47 2016 July 1530 1620 48 2016 August 1620 1530 49 2016 September 1560 1620 50 2016 October to be forecast 1560 51 2016 November to be forecast 1560 52 2016 December to be forecast 1550 53 54 55 Naive 56 MAD 93.3333333 57 58 59 Difference 0% ANAME? 0% 0% 0% 0% 0% 0% 0% O% Forecasts MA 1778 1748 1710 1650 1628 1665 1658 1535 1613 1583 1570 1590 Trendline Time Index Actual Observations 1 1560 2 1680 3 1710 4 1740 5 1680 6. 1752 7 1680 8 1560 9 1650 10 1800 11 1860 12 1800 13 1530 14 1650 15 1620 16 1710 17 1680 18 1620 19 1530 20 1620 21 1560 22 to be forecast 23 to be forecast to be forecast Naive Absolute Forecast for MA ES Trendline ES FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 8888888 120 30 00 30 50 90 90 50 + Forecasts MA ES Trendline Student Name Forecasting Data and Template Ready . Calibri - 11-AAE BIU-- General Normal El Mergea Center - $ 969 Ciboard Font Forming Alignment be C D E F O Dema Time series plot Tras More 2015 January 2016 Februar Man 1680 1710 Actual Observations ISO 1710 8 9 y24 13 May + 2020 June Jul 1580 9 2002 70 2021 September Genober 1800 12 2005 November 2006 December 14 302 January 1530 15 7024 February 16 2020 March 152 77 200 April 1710 18 21 May 19 2020 June 1620 July 21 2034 August SOOD 22 2015 September 1560 21 2015 October to be forca 24 2037 November habe forca 25 2009 December to be forecast 26 M 2015 Lamar 2005 Feb 2012 March April 2009 May 2020 2021 2022 A 20173 pembe 2014 October 2005 November 2006 December 200 January 2001 2009 Math 20 Apr 2013 My 2012 July 2054 2055 pembe 2055 October 2017 November 2018 December 2 . 12 1 12 18 10 19 20 21 ISSO 1560 to before to be fout to be forecast Difference 1560 AME 29 2025 Lanuary 30 2015 February 51 2015 March 32 2015 113015 May 2015 June 1550 1660 1710 1740 10 1752 os 36 2015 August Professor, Inputed the correct rendline even though I can't get 1050 1800 1860 0% ON Time index cual Observations 1560 2 160 5 1710 1740 5 179 2 1680 1 1560 9 10 1800 11 1860 12 11 1530 14 16 16 36 1710 12 18 MA ES Trendine Trendline 2015 October 2015 November 20 2015 December 41 2016 January 42 2016 February 41 2016 March 44 2016 45 2016 May Na 270 130 FALL 1650 10.30 1650 R&RS 30 90 30 16BD Student Name AL 34 Forecasting Data and Template c CA