Bayesian Analysis

Bayesian Analysis Definition

The goal of Bayesian analysis is “to translate subjective forecasts into mathematical probability curves in situations where there are no normal statistical probabilities because alternatives are unknown or have not been tried before” (Armstrong, 2003:633). Bayesian analysis aims to update probabilities in the light of new evidence via Bayes' theorem (Jackman, 2009).

Bayesian Analysis Description *

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Strengths, weaknesses and examples of Bayesian Analysis *

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Implementation, success factors and measures of Bayesian Analysis *

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Bayesian Analysis videos and downloads *

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Bayesian Analysis web and print resources *

Bayesian Analysis references (4 of up to 20) *

• Andrews, M. and Whittaker, J.A. (2006) How to Break Web Software. Pearson Education, Boston, MA.
• Armstrong, M. (2003) A Handbook of Management Techniques. Kogan Page, London.
• Beri, G.C. (2008) Marketing Research. Tata McGraw-Hill, New Delhi.
• Blattberg, R.C., Kim, B.-D. and Neslin, S.A. (2008) Database Marketing: Analyzing and Managing Customers. Springer, New York.

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