1. A. Judgment Heuristics Definition: Rule of thumb; quick decision guide When are heuristics used? - When making intuitive judgments about relative likelihoods (e.g., “business gambles”). 1. Will Mr. Jones or Ms. Smith be a better marketing VP? 2. Will a non-sugar coated cereal sell better than the usual breakfast fare? 3. How likely is it that next year’s unemployment rate will exceed 8%?

2. Judgment Heuristics Advantages: 1. Reduce task complexity 2. Functional & cost effective 3. Often work well Disadvantages: 1. Can lead to errors 2. We often don’t realize we’re using them 3. Errors may persist even when we ARE aware (and even when the stakes are high)

3. Availability People assess the frequency of an event by the ease with which instances or occurrences can be brought to mind. - Usually a good heuristic since frequent events ARE typically easier to recall then less frequent events. AVAILABILITY DANGERS: 1. Redundancy 2. Salience (familiarity, recentness, emotional content) 3. Selective exposure 4. Imaginability (leads to underestimation of failure probabilities

4. Probability of dying from: Lung cancer(75,000) Motor Vehicle Accident(55,000) actual ratio: 1.3 : 1 Emphysema(21,000) Homicide(19,000) actual ratio: 1.15 : 1 Asthma(1840) Tornadoes (88) actual ratio: 21 : 1

5. Representativeness Probabilities are evaluated by the degree to which A is representative of or resembles B or C. Probabilities judgments are reduced to judgment of similarity. - When A is highly representative of B, the probability that A originates form B (or is a member of B group) is judged to be high.

6. Representativeness Advantages: 1.Easy to use. 2. Natural to think in terms of similarities. 3. Functional and often accurate (stereotypes). Dangers: 1. Prior probabilities (base rates) ignored. a) lawyer-engineer problem b) Linda problem 2. Reliability of the evidence ignored. - matching predictions to impressions may be unsound since such a procedure fails to take uncertainty (re: diagnositicity of impression cues) into account.

7. 80 engineers and 20 lawyers were interviewed, and were described with thumbnail descriptions. The following descriptions have been drawn at random from the sample of 80 engineers and 20 lawyers. John: John is 39 years old. He is married and has two children. He is active in local politics. The hobby that enjoys the most is rare book collecting. He is competitive, argumentative and articulate. Q: What is the probability that John is a lawyer? Dick: Dick is 30 years old. He is married with no children. A man of high ability and high motivation, he promises to be quite successful in his field. He is well liked by his colleagues. Q: What is the probability that Dick is a lawyer?

8. Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social injustice, and also participated in antinuclear demonstrations. Which one of these is more probable? (a) Linda is bank teller (b) Linda is a bank teller and active in the feminist movement FeministBank teller

9. Stephen J. Gould (1992, p. 469) I am particularly found of [the Linda] example, because I know that the [conjunction] is least probable, yet a little homunculus in my head continues to jump up and down, shouting at me -- ‘but she can’t just be a bank teller; read the description’… Why do we constantly make this simple logical error? Tversky and Kahneman argue, correctly I think, that our minds are not built (for whatever reason) to work by the rules of probability.

10. Anchoring and Adjustment In estimating an unknown quality, we start with some convenient initial value and adjust in particular direction. - often used when a relevant value is available (e.g., next year’s budget, inflation rate, GPA) Anchoring & Adjustment Dangers: 1. Insufficient adjustment (anchors weighted too heavily) 2. Underestimating disjunctive events (“or”) - e.g., nuclear power plant failure. 3. Overestimating conjunctive events (“and”) - e.g., new project success 4. Inappropriate anchors