Polish Version
Anna Borucka
Summary
Objective– Twomethods of predictionwereproposed in the article, usingsales data. Modelswereidentified and estimated, forecastsweredetermined, theirreliability was verified, and thenvaluesobtained for eachmethodwerecompared.
Methodology – The article presents models belonging to two different categories. They are regression function, which is a classic example of cause-and-effect model, and ARIMA model for time-series analysis.
Results– The results obtained for both models were satisfactorily described by empirical data, but the regression model is much easier to estimate and does not require complex transformations orcalculations, nor the use of specialized software. In the analyzed case, demand forecasting based on the linear regression model is sufficient and reflects the nature of studied phenomenon.
Analysis of the effectiveness of selected demand forecasting models
Article
In order to view this page you need Flash Player 9+ support!
