DESIGN AND IMPLEMENTATION OF COMPUTERIZED BUSINESS FORECASTING SYSTEM USING REGRESSION ANALYSIS. A RESEARCH PROJECT MATERIAL ON COMPUTER SCIENCE
As the strategic planner bogs is mind with trying to predict the future performance of some available variable qualitatively, at the mercy of human limitations and time constraint.
The COMPUTERIZED FORECASTING TECHINIQUES comes not only to increase his speed of operation but to save him the trouble of determining which method to use and if so applied assures of reliability of such forecast.
The features of this package include
1. Ability to choose from the various quantitative forecasting techniques.
3. finally a help path, which includes documentation on the software loading the Pascal computer.
1.1 OVERVIEW OF FORCASTING TECHNIQUES.
Right from the time life started, till now, man ahs sought to forecast the future. Things that happened before are used to justify what will take place in the future. Most of the times, it becomes true while at other time it facts. The ability to forecast the consequence of actions and events is one of the defining properties of the mind.
In any business situation, it is necessary to be able to make some predictions about the future in order to make some predictions about the future in order to plan the business operations well-Arriving at such an climate of the future is the purpose of the process of forecasting.
In the service sector, a forecast of demand for the service being offered is necessary to determine the number of staff that will be sufficient enough for the business and the quantity of raw materials to be bought.
In the retailing sectors, forecast of sales will be needed to decide staffing levels and also to determine what qualifies of stock should be purchased. Excessive levels of stock tie up working capital and storage space, further expenses can be incurred through such process as theft, insurance and possibly, deterioration. On the other head, inadequate re-order quantities such as high, ordering cost and the inability to meet customers demand.