M.Com. (Business Management) / Forecasting is an important function used in a wide range of business planning or decision-making situations. The purpose ofthis study was to build a sales forecasting model that would be practical and cost effective, from the various forecasting methods and techniques available. Various forecast models, methods and techniques are outlined in the initial part of this study by the author. The author has outlined some of the fundamentals and limitations that underline the preparations of forecasting models. It is not the purpose of this study to microscopically dissect each forecasting model, method or technique. Various forecasting options were assessed in a manner that could provide some relevance to the study, thus providing a general framework for the construction of the specific sales forecasting model. Appropriate data sources were described and analysed. The data was further tested using the author's chosen quantitative forecasting techniques. Results were interpreted, and included into the author's untested sales model. It is the author's opinion that the sales model is practical, cost effective and gives a general sales forecast.

M.Com. (Economics) / The main purpose of this study was the descriptive analysis and theoretical evaluation of various economic forecasting techniques applicable to a wide variety of forecasting problems. A comprehensive review was given of the basic structure of the techniques (theory and mechanics). their appropriateness ,In different forecasting circumstances, their technical and other limitations, advantages and disadvantages, together with a guide to the better understanding and interpretation of their results. Many of the problem areas related to economic forecasting can be avoided or at least alleviated, by a proper study of the adequacy and other distinguishing characteristics of a specific forecasting methodology. Forecasting accuracy is a major interest of anyone concerned with the future. There are many different ways of saying that the future belongs to those who plan for It best. This Is certainly true in economics as the practice thereof is filled with uncertainties. The topic of this dissertation is, therefore, very relevant In today's modern world. Diagnosis and forecasting have become inevitable with the growth of the" risk factor" In this world. Efforts are constantly made to eliminate, neutralize or at least decrease as far as possible, the risk attendant to this uncertainty by accurately predicting the future values of important variables. The importance and need for improved economic forecasting has, without a doubt, grown tremendously in recent years. The list of forecasting application Is quite lengthy as virtually every important operating decision depends to some extent on a forecast. Probably the simplest definition of forecasting is that it Is a process which has as its objective the explaining and prediction of events or conditions which will occur at some future time. More precisely, economic forecasting attempts to predict the change In Important economic phenomena. The forecast must however not be seen as an end product, but rather as an ongoing process of input In the decision-making process. Forecasting Is both an art and a science, but although II is a form of art it Is not without structure. As with any worthwhile art form. the forecasting process Is definitive and systematic. A number of special tools and techniques can be used In predicting the future " values of economic variables. The objective selection among these forecasting techniques is extremely difficult. The many different types of forecasting methods available can be grouped into two main categories: (i) the qualitative forecasting methods and (II) the quantitative methods.

system model and computational methodology have been developed which evaluate the worth of flood forecast - response systems in reducing the economic damage caused by floods. The efficiencies of the forecast system, the response system, and the overall system may be individually obtained and compared. In this report the case study of Milton, Pennsylvania, was extended and further case studies were performed including a large residential section of Victoria, Texas, and all the residences in Columbus, Mississippi. These locations show better forecast and response efficiencies than obtained for Milton, Pennsylvania. The difference is attributed to longer forecast lead times at Columbus and Victoria. Sensitivity analyses were run at all three locations. These show the effects of many system factors, such as the time required to produce, disseminate and respond to a forecast, on the efficiency of the system. The forecast efficiency improves significantly as these times are reduced. Further analysis of the response system based on human factors involved has led to the development of a simulation model of the process by which the floodplain dweller determines the appropriate response to a flood warning. Investigation of ways to extend the methodology to evaluate regions lacking the detailed data used for the case studies has indicated more problems than answers. Extrapolation based on overall system efficiency related to published regional and national flood damage estimates was used to provide an approximate value of the flood forecast - response system for two regions and for the nation.A listing of simplicities and approximations which make computations tractable but which may affect accuracy is given. Finally, an evaluation of the work accomplished for this project and suggestions for the constructive use of the flood forecast -response system model and computational procedures is given.

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