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Forecast for 21 TV Sales Yasmine Yahia Mohamed Tantawi Ossama Kamal Yasser Abd-Elbary Under Supervision: Prof. Sayed Elkholy QA– ESLSCA_29B 25 October.

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Presentation on theme: "Forecast for 21 TV Sales Yasmine Yahia Mohamed Tantawi Ossama Kamal Yasser Abd-Elbary Under Supervision: Prof. Sayed Elkholy QA– ESLSCA_29B 25 October."— Presentation transcript:

1 Forecast for 21 TV Sales Yasmine Yahia Mohamed Tantawi Ossama Kamal Yasser Abd-Elbary Under Supervision: Prof. Sayed Elkholy QA– ESLSCA_29B 25 October 2009

2 Simple Moving Average Weighted Moving Average Smoothing Forecast Seasonal Index Comparison Contents

3 Simple Moving Average MonthActual Sales (2008) Actual Sales (2009) SMA (3months) SMA (4months) SMA (6months) Jan41004286 Feb26552978 Mar32213689 Apr21002200 May22502460 Jun31503396 Jul33473788 Aug45505788 Sep33673870 Oct2116448242113584 Nov3245 Dec4760

4 Weighted Moving Average MonthActual Sales (2008) Actual Sales (2009) W i (0.74) AiWiAiWi Jan410042860.106452.90 Feb265529780.068203.40 Mar322136890.082304.25 Apr210022000.054119.10 May225024600.058142.65 Jun315033960.081275.70 Jul334737880.086327.06 Aug455057880.117678.75 Sep336738700.086334.14 Oct21160.0543836.63 Nov32450.084 Dec47600.122

5 Smoothing Forecast SF t+1 =SF t + α(A t -SF t ) MonthActual Sales (2008) Actual Sales (2009) SF ( α =0.2) SF ( α =0.5) SF ( α =0.85) Jan41004286 Feb265529784286 Mar32213689402436323174 Apr21002200395736613612 May22502460360629302414 Jun31503396337726952453 Jul33473788338130463255 Aug45505788346234173708 Sep33673870392746025476 Oct2116391642364111 Nov3245 Dec4760

6 Seasonal Index Month X Actual Sales (2008) Y X2X2 Y2Y2 XY Jan 14100116,810,0004,100 Feb 2265547,049,0255,310 Mar 33221910,374,8419,663 Apr 42100164,410,0008,400 May 52250255,062,50011,250 Jun 63150369,922,50018,900 Jul 733474911,202,40923,429 Aug 845506420,702,50036,400 Sep 933678111,336,68930,303 Oct 1021161004,477,45621,160 Nov 11324512110,530,02535,695 Dec 12476014422,657,60057,120 7838,861650134,535,545261,730

7 Seasonal Index … Continue Y = a + bX b = (n ΣXY – ΣX ΣY)/(n ΣX 2 –(ΣX) 2 ) a = (ΣY – b ΣX) / n ΣX = 78; ΣY = 38,861; ΣX2 = 650; ΣY2 = 134,535,545; ΣXY=261,730 b = 63.87; a = 2,823.3 Y = 2823.3 + 63.87 X

8 Month X Actual Sales (2008) Y YY\Y Jan 141002,887.171.420 Feb 226552,951.040.900 Mar 332213,014.911.068 Apr 421003,078.780.682 May 522503,142.650.716 Jun 631503,206.520.982 Jul 733473,270.391.023 Aug 845503,334.261.365 Sep 933673,398.130.991 Oct 1021163,462.000.611 Nov 1132453,525.870.920 Dec 1247603,589.741.326 Seasonal Index … Continue

9 Month X Sales Forecast (2009) Y Y/Y From 2008 Sales Forecast Oct 09 224,228.440.6112584 Nov 09 234,292.310.9203950 Dec 09 244,356.181.3265776 By applying Y for remaining months and use Y/Y from 2008 data for its equivalent months, we got the below table: Note: we couldnt have ASI, as we have only year data Seasonal Index … Continue

10 Seasonal Index … another calculations Month X Y (2008 & 2009) X2X2 Y2Y2 XYYY/Y Jan 08 14100116,810,0004,1002913.551.407 Feb 08 2265547,049,0255,3102961.800.896 Mar 08 33221910,374,8419,6633010.051.070 Apr 08 42100164,410,0008,4003058.30.687 May 08 52250255,062,50011,2503106.550.724 Jun 08 63150369,922,50018,9003145.800.998 Jul 08 733474911,202,40923,4293203.051.046 Aug 08 845506420,702,50036,4003251.301.399 Sep 08 933678111,336,68930,3033299.551.020 Oct 08 1021161004,477,45621,1603347.800.632 Nov 08 11324512110,530,02535,6953396.050.956 Dec 08 12476014422,657,60057,1203444.301.382 Jan 09 13428616918,369,79655,7183492.551.227 Feb 09 1429781968,838,48441,6923540.800.841 Mar 09 15368922513,608,72155,3353589.051.028 Apr 09 1622002894,840,00035,2003637.300.605 May 09 1724603246,051,60041,8203685.550.667 Jun 09 18339636111,532,81661,1283733.800.910 Jul 09 19378840014,348,94471,9723782.051.002 Aug 09 20578844133,500,944115,7603830.301.511 Sep 09 2138703,31114,976,90081,2703878.550.998 23171,316260,633,750821,625

11 Month X Sales Forecast (2009) Y Y/Y From 2008 Sales Forecast Oct 09 223,926.800.6322481.96 Nov 09 233975.050.9563798.25 Dec 09 244023.301.3825560.17 Y = a + bX b = 48.25; a = 2,865.30 Y = 2865.3 + 48.25 X By applying Y for remaining months and use Y/Y from 2008 data for its equivalent months, we got the below table: Note: we couldnt have ASI, as we have only year data Seasonal Index … another calculations

12 Comparison OctNovDec SMA (3months) 4482 SMA (4months) 4211 SMA (6months) 3584 WMA3837 SF ( α =0.2) 3916 SF ( α =0.5) 4236 SF ( α =0.85) 4111 Seasonal Index (1 st Calculations) 258439505776 Seasonal Index (2 nd Calculations) 248237985560


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