Business forecasting in the light of statistical approaches and machine learning classifiers

Abstract

The paper focuses a non-conventional approach using Poisson and Binomial distributions for optimum strategic business forecasting. An analysis has been carried out based on profit-loss statistics of consecutive ten years. Relevance of Poisson distribution in business forecasting is shown. Relevance of Binomial distribution in business forecasting is also shown. Curve fitting has been applied to reveal further some discovered facts related to gain analysis. Linear Regression, Exponential, Parabolic, Power function, Logarithmic, polynomial of degree 2 and 4 curves are shown as cases. Novel facts related to business forecasting in the light of machine learning classifiers have been pointed out leading to new directions in the field of research in business analytics.