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Comparison and Contrast of Forecast Methods

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Comparison and Contrast of Forecast Methods
Comparison and Contrast of Forecast Methods

MGT 554
Operations Management

University of Phoenix
Professor Leonard Enger
May 1, 2006

TABLE OF CONTENT

Cover Page……………………………………………………….1
Table of Contents………………………………………………...2
Seasonal Forecasting……………………………………………..3
Delphi Method……………………………………………………4
Technological Method……………………………………………5
Time-series forecasting…………………………………………...6
Company Forecasting Methods…………………………………..7
Conclusion………………………………………………………..8
References………………………………………………………..9

Comparison and Contrast of Forecast Methods

There are several different methods that can be used to create a forecast, this paper will compare and contrast the Seasonal, Delphi, Technological and Time Series method of forecasting. Factors to consider when selecting a forecast method is the experience of the forecaster, the amount of information available, the degree of accuracy or confidence needed from the forecast and the level of difficulty that the situation present.
Forecasting is the process of estimating or predicting future events or conditions. Forecasts may be long-term or short-term. The techniques used may be quantitative or qualitative. Quantitative forecasting models may be classified into (a) causal models in which independent variables are used to forecast dependent variables, and (b) time series models, which produce forecasts by extrapolating the historical values of the variables of interest by, eg, moving averages. www.indiainfoline.com/bisc/accf.html
Seasonality Forecasting
Seasonality is often displayed by time series forecasting. Seasonality can be simply described by periodic fluctuations. Seasonality is less common in engineering and scientific data but is commonly used in economic time series. Retail sales tend to peak for holiday seasons and then decline after the holidays. So time series of retail sales will typically show increasing sales from September through December and declining sales in January and February.
If seasonality is



References: Decisioneering, Inc., (2000-2005) http://www.decisioneering.com/time-series-forecasting.html Nirlon Complex, Off W E Highway, Goregaon(E) Mumbai-400 063 (2005) www.indiainfoline.com/bisc/accf.html StatSoft, Inc., (1984-2003), Electronic Textbook Statsoft http://www.statsoft.com/textbook/sttimser.html#systematic

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