文档介绍：CHAPTER 19: Decision Theory
to pany
Introduction to Business Statistics
fourth edition, by Ronald M. Weiers
Presentation by Priscilla Chaffe-Stengel
Donald N. Stengel
© 2002 The Wadsworth Group
Chapter 19 - Learning Objectives
Express a decision situation in terms of decision alternatives, states of nature, and payoffs.
Differentiate between non-Bayesian and Bayesian decision criteria.
Determine the expected payoff for a decision alternative.
Calculate and interpret the expected value of perfect information.
Express and analyze the decision situation in terms of opportunity loss and expected opportunity loss.
Apply incremental analysis to inventory-level decisions.
© 2002 The Wadsworth Group
Chapter 19 - Key Terms
Levels of doubt
Risk
Uncertainty
Ignorance
Decision situation
Decision alternatives
States of nature
Probabilities
Expected payoff
Maximin criteria
Maximax criteria
Minimax regret
Expected value of perfect information
Expected opportunity loss
Incremental analysis
© 2002 The Wadsworth Group
The Decision Situation
The decision maker can control which decision alternative (row) is selected but cannot determine which state of nature (column) will occur.
The decision alternative is selected prior to knowing the state of nature.
© 2002 The Wadsworth Group
An Example
Problem : A ski resort operator must decide before the winter season whether he will lease a snow-making machine. If he has no machine, he will make $20,000 if the winter is mild, $30,000 if it is typical, and $50,000 if the winter is severe. If he decides to lease the machine, his profits for these conditions will be $30,000, $35,000, and $40,000, respectively. The probability of a mild winter is , with a chance of a typical winter and a chance of a severe winter. If the operater wants to maximize his expected profit, should he lease the machine? What is the most he should be willing to pay for a perfect forecast?
© 2002 The Wadsworth Group
The Decision Situation: