Decision Making and Reasoning

1. Decision Making and Reasoning Chapter 12

2. Outline • Judgment and Decision Making • Classical Decision Theory • Satisficing • Elimination by Aspects • Heuristics and Biases • Deductive Reasoning • Conditional Reasoning • Inductive Reasoning

3. 1. Judgment and Decision Making • The goal of judgment and decision making is to select from among choices or to evaluate opportunities 1. Classical Decision Theory • Based on the assumption or rationality • People make their choices so as to maximize something of value, whatever that something may be • Mathematical models of human decision making • Too restricted, does not take into account the psychological makeup of each individual decision maker

4. 1. Judgment and Decision Making 1. Classical Decision Theory • Subjective expected utility theory • The goal of human action is to seek pleasure and avoid pain; in doing so each of us uses calculations of • Subjective utility – based on the individual’s judged weightings of utility, rather than on objective criteria • Subjective probability – based on the individual’s estimates of likelihood, rather than on objective statistical computations

5. 1. Judgment and Decision Making 1. Classical Decision Theory • This theory is based on the belief that people seek to reach well-reasoned decisions based on • Consideration of all possible known alternatives • Use of a maximum amount of available information • Careful weighing of costs and benefits and calculation of probability • A maximum degree of sound reasoning • However, human decision making is more complex than even this modified theory implies

6. 1. Judgment and Decision Making 2. Satisficing • We humans are not entirely and boundlessly rational in making decisions • Bounded rationality • We are rational, but within limits • Satisficing • We do not consider all possible options and then carefully compute which of the entire universe of options will maximize our gains and minimize our losses • Rather, we consider options one by one, and then we select an option as soon as we find one that is satisfactory or just good enough to meet our minimum level of acceptability

7. 1. Judgment and Decision Making 3. Elimination by Aspects • We sometimes use a different strategy when faced with far more alternatives than we feel that we reasonably can consider in the time we have available • Elimination by aspects • We focus on one aspect (attribute) of the various options, and we form a minimum criterion for that aspect • We then eliminate all options that do not meet that criterion

8. 1. Judgment and Decision Making 4. Heuristics and Biases • Amos Tversky and Daniel Kahneman • People may be far more likely to make decisions based on biases and heuristics (short-cuts) than earlier decision-making research has suggested • These mental shortcuts lighten the cognitive load of making decisions, but they also allow for a much greater chance of error

9. ? All the families having exactly six children in a particular city were surveyed. In 72 of the families, the exact order of births of boys and girls was GBGBBG (G girl; B boy). What is your estimate of the number of families surveyed in which the exact order of births is BGBBBB?

10. 1. Judgment and Decision Making 4. Heuristics and Biases • Representativeness • When we use the heuristic of representativeness, in which we judge the probability of an uncertain event according to • (1) how obviously it is similar to or representative of the population from which it is derived • (2) the degree to which it reflects the salient features of the process by which it is generated • Example on the previous slide • First birth order is considered to be more representative of the number of females and males in the population • However, either birth order is equally likely to occur by chance

11. ? Are there more words in the English language that begin with the letter R or that have R as their third letter?

12. ? • Calculate in your head the answer to the following problem: 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1

13. ? • Calculate in your head the answer to the following problem: 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8

14. 1. Judgment and Decision Making 4. Heuristics and Biases • Availability • We make judgments on the basis of how easily we can call to mind what we perceive as relevant instances of a phenomenon (e.g. words beginning with letter R) • Anchoring-and-adjustment heuristic • People provide a higher estimate for the first sequence than for the second because their computation for the the anchor – the first few digits multiplied by each other – renders a higher estimate from which they make an adjustment to reach a final estimate

15. 1. Judgment and Decision Making 4. Heuristics and Biases • Overconfidence • And individual’s overvaluation of her or his own skills, knowledge, or judgments • People tend to overestimate the accuracy of their judgments • Example: • When people were 100% confident in their answers, they were right only 80% of the time

16. 2. Deductive Reasoning • Proposition • An assertion, which may be either true of false • Premise • Propositions about which arguments are made

17. 2. Deductive Reasoning 1. Conditional Reasoning • The reasoner must draw a conclusion based on an if-then proposition • Deductive validity • Does not equate with truth • You can reach deductively valid conclusions that are completely untrue with respect to the world • People are more likely mistakenly to accept an illogical argument as logical if the conclusion is factually true

18. 2. Deductive Reasoning 1. Conditional Reasoning • Modus ponens • The reasoner affirms the antecedent If p then q p q • Modus tollens • The reasoner denies the consequent If p then q non q non p

19. 2. Deductive Reasoning 1. Conditional Reasoning • Deductive fallacies • Denying the antecedent • Affirming the consequent • Rather then using formal inference rules, people often use pragmatic reasoning schemas

20. 2. Deductive Reasoning 2. Syllogistic Reasoning • Syllogisms • Are deductive arguments that involve drawing conclusions from two premises • All syllogisms comprise a major premise, a minor premise, and a conclusion

21. 2. Deductive Reasoning 2. Syllogistic Reasoning • Linear Syllogisms • The relationship among the terms is linear, involving a quantitative or qualitative comparison • Example • You are smarter than your best friend. • Your best friend is smarter than your roommate. • Which of you is the smartest?

22. 2. Deductive Reasoning 2. Syllogistic Reasoning • Categorical Syllogisms • Comprise of two premises and a conclusion • The premises state something about the category memberships of the terms • Example: • All cognitive psychologists are pianists. • All pianists are athletes. • Therefore, all cognitive psychologists are athletes.

23. 3. Inductive Reasoning • In inductive reasoning, which is based on our observations, reaching any logically certain conclusion is not possible • The most we can strive to reach is only a strong, or highly probable, conclusion • A key feature of inductive reasoning, which forms the basis of the empirical method, is that we cannot logically leap from saying, “ all observed instances to date of X are Y” to saying, “Therefore, all X are Y”; it is always possible that the next observed X will not be a Y

24. 3. Inductive Reasoning • Causal inferences • How people make judgments about whether causes something else • Errors in inductive reasoning • Confirmation bias • Teachers often expect little of students when they think them low in ability • Causality based on correlational evidence alone • We fail to recognize many that many phenomena have multiple causes

25. 3. Inductive Reasoning • Reasoning by analogy • Example Fire is to asbestos as water is to • Vinyl • Air • Cotton • faucet