Decision Making Under Uncertainty

Designed primarily to introduce the graduate business student to the Bayesian decision-making process in business and industry. The theoretical basis for making decisions and the components of the business decisions process are defined. Current methods, including subjective probability, payoff functions, utility theory, and criteria for selection of alternative actions are introduced. Special emphasis is placed on the solution of actual problems in production and distribution through the construction of quantitative models.