From the provided Spreadsheet Identify the four types of Forecasts and explain w

Question

From the provided Spreadsheet Identify the four types of Forecasts and explain which one is the best and why .

Copy of Copy of ISOM 251 forcasting worksheet assignment data 2018(1)-Last Saved 4/15/2013 1:16PM ? Tyler Fisher x Insert Page Layout FormulasData Review View Help Tell me what you want to do 10,1 A'a" 9-2? Wrap Text Copy Paste B 1 u ii- ??· ?? ? ? ? Merge & Center· s-% , ?f: Conditional Fomat as Cell Insert Delete Format Fomatting Table Styles Sort & Find & Filter Select Fonmat Painter Font Alignment Number Editing P4 examples Assignment ACTUAL Price of Gasoline lag one week Lag two? Nov 28, 1994 Dec 05, 1994 Dec 12, 1994 Dec 19. 1994 Dec 26, 1994 Jan 02. 1995 Jan 09. 1995 Jan 16, 1995 Jan 23, 1995 Jan 30, 1995 Feb 06, 1995 Feb 13, 1995 Feb 20. 1995 Feb 27, 1995 Mar 06, 1995 1.197 13 Section 3: Cost 14 Table 3-2Trend: Cost Breakdown by Category by Year* 15 Cost Type 16 Depreciation 17 Maintenance 18 Indirect 19 Comm. Lease 20 GSA Lease 21 Fuel 22 Total 23 GSA Lease Cost above includes fuel. The line for Fuel therefore is only for non-GSA Fleet vehicles 1.197 $2,007 454.961.958 $1,178,098,959 $116,981,219 70,997,729 S1,033,299.118 $701.188.135 S3,555,527,118 $523,648.384 $1,350,558,809 $132,661,776 72,258,881 $1,115,912,974 5910,092,639 $4,105,133,464 $591.492.853 S890.121,517 $1,197,856,339 $1,203,848,657 $150,078,649 S397,683,481 $78,938.099 S72,307,833 $1,098.311.931 $1.140.911,564 $644,278,341 S888,400,204 S3,760,956,212 $4,593,273,256 S1.040,616,069 $962,801,608 $252,824,284 $72,971,037 S1,113,145.205 $999.016.185 S4,441,374,388 Assignment! ? ?- + 100% 1:38 PM O Type here to search 4/15/2018 2

Explanation / Answer

Ans: The above question has used Time Series Forecasting Method. A time series forecast is based on the equally spaced data points e.g. weekly, monthly, annually.

The 4 types of time series forecasting:

Among the 4-time series methods, exponential smoothing is considered as best method because it required very little past data and easy to use.

New Forecast = Last period’s forecast + ? (last period actual demand – last period’s forecast)

Where, ? is the smoothing constant and has value ? 0 ?1.

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