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.
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Aaker, D.A.: Strategic Market Management. Wiley, New Jersey (2005)
Levitt, T.: Marketing Myopia. Harvard Business Review, pp. 45–56, July–August (1960)
Olofsson, P.: Probability, Statistics, and Stochastic Processes. Wiley, New Jersey (2005)
Giri, P.K., Banerjee, J.: Introduction to Statistics. Academic Publishers, Cambridge (1999)
Mitchell, T.M.: Machine Learning. Tata McGraw Hill Companies, Inc., New York (1997)
Cobb, C.W., Paul, D.H.: A theory of production. Am. Econ. Rev. Suppl. 18, 139–165 (1925)
Samuelson, A.P.: Economics, 10th edn. McGraw-Hill Book Company, New York (1976)
Hanke, J.E., Wichern, D.W.: Business Forecasting. Pearson Education Inc., London (2009)
Gordon, G.: System Simulation. Pearson Education, Inc., London (1978)
Casella, G., Berger, R.L.: Statistical Inference. Duxbury Advanced Series Thomson Learning, Pacific Grove (2002)
Tony, M.: Principles of Strategic Management. Taylor & Francis, London (2007)
Udo, S., Len, T., Michael, G.: Business Forecasting. Wiley, New York (2016)
Shwartz, S.S., David, S.B.: Understanding Machine Learning: From Theory to Algorithms. Cambridge University Press, Cambridge (2014)
Agresti, A.: Categorical Data Analysis. Wiley, New York (1990)
Richard, R.: Data Mining: A Tutorial-Based Primer. CRC Press, New York (2016)
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Chakrabarti, P., Satpathy, B., Bane, S., Chakrabarti, T., Chaudhuri, N.S., Siano, P. (2019). Business Forecasting in the Light of Statistical Approaches and Machine Learning Classifiers. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T., Kashyap, R. (eds) Advances in Computing and Data Sciences. ICACDS 2019. Communications in Computer and Information Science, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-13-9939-8_2
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DOI: https://doi.org/10.1007/978-981-13-9939-8_2
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