Paper Title
Demand Curve Prediction with Multivariate Bayesian Analysis: A Graphical Approach

Bayesian analysis refers to the process of assessing the current state of knowledge (the prior information), gathering new information (in any form such as experiments or data), and updating the prior belief to get a posterior belief that incorporates the observed information into the prior belief. This process of Bayesian updating has had a wide range of applications including scientific inquiry, clinical testing, criminal justice, public policy, and even developing new e-mail spam filters. This tutorial presents an overview of Bayesian analysis within the context of demand estimation in systems engineering. An introduction to multivariate Bayesian updating using graphical methods; conjugate priors, and the value of information is provided. Emphasize is on demand estimation and belief updating graphically updating a prior distribution given the results of one more polls.