1. Chapter 8: Decision Making

2. Classes AND FEATURES OF DM

3. Uncertainty
Time
Familiarity and Expertise
Classes of DM research

4. AN INFORMATION PROCESSING MODEL OF DECISION MAKING

6. WHAT IS “GOOD’ DECISION MAKING?

7. DIAGNOSIS AND SITUATION ASSESSMENT IN DECISION MAKING

8. Estimating Cues: Perception
Proportions
Projections
Randomness
Gambler’s fallacy

9. Evidence Accumulation, Selective Attention: Cue Seeking and Hypothesis Formation

10. Evidence Accumulation, Selective Attention: Cue Seeking and Hypothesis Formation
Information cues are missing
Cues are numerous: Information overload
Cues are differently salient
Salient bias, absence of cue

11. Evidence Accumulation, Selective Attention: Cue Seeking and Hypothesis Formation
Processed cues are not differentially weighted by information value
As-if heuristic

12. Expectations in Diagnosis: The Role of Long-Term Memory
Representativeness
Base rate
The availability heuristic

13. Belief Changes Over Time
Anchoring heuristic
The confirmation Bias
Cost of thinking, motivational factors (consistency), self-fulfilling prophecy
Decision fatigue

14. CHOICE OF ACTION

15. Certain Choice

16. Choice Under Uncertainty: The Expected Value Model

17. Heuristics and Biases in Uncertain Choice
Direct retrieval
Distortions of values and costs: Loss aversion

18. Heuristics and Biases in Uncertain Choice
Temporal discounting
Perception of probability
The framing effect

19. EFFORT AND META COGNITION

20. Effort
Performance-resource function
Contingent model

21. Meta-Cognition and (Over) confidence
Diagnostic or problem difficulty
Evidence reliability

22. Experience and Expertise in DM
Holistic decision making
expertise

23. Experience and Expertise in DM

24. Improving Decision Making
Training debiasing
Proceduralization
Displays
Automation and Decision Support Tools