Judgment and Decisions. Judgment: “how likely is that …?” Decision-Making (Choice): ‘should you take a coupon for $200 or $100 in cash, given that …”

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Presentation transcript:

Judgment and Decisions

Judgment: “how likely is that …?” Decision-Making (Choice): ‘should you take a coupon for $200 or $100 in cash, given that …” Heuristic: - a ‘rule of thumb’ for judgment and decision-making - it takes into account only a portion of the available evidence - it allows for fast and efficient decision-making, but -it is vulnerable to error. -Representativeness heuristic -Availability heuristic -Anchoring heuristic

William has been randomly selected for an interview. From the interview, the following personal info was revealed: William is a short, shy man. He has a passion for poetry, and loves strolling through art museums. As a child, he was often bullied by his classmates. 1.farmer 2.Classics scholar

Why? similarity: he sounds like a classics scholar

Michael has been randomly selected for an interview. Do you suppose that Michael is: 1.Older than 88 ys 2.Younger than 88 Why?

The Representativeness Heuristic The tendency to judge an event as likely if it “represents” the typical features of its category. (individual is similar to the prototype) Why is it useful? - Typical features often are the most frequent ones Why is it sometimes misleading? - It fails to account for: - prior odds - Base Rate Neglect

Base Rate: Some things are very frequent (flu), others are quite infrequent (mad cow disease) Base Rate Neglect: tendency to neglect the overall frequency of an event when predicting its likelihood.

A single witness is found for a hit and run accident involving a taxi cab. There are 2 cab companies in this town. A huge blue cab company (with 1000 cars active at a time) and, A small green cab company (with 50 cars active at a time). The witness believes the cab was green. Subsequent experiments show that this person is 90% accurate in determining the color of cabs. Is it more likely that the cab was blue or green? Base Rate Neglect: People’s tendency to neglect the overall frequency of an event when predicting its likelihood. Base Rate Neglect: Example

More likely to be a green car. Do you agree? 1.Yes 2.No

1000 blue cabs Suppose the witness were to identify all the cabs in the city green cabs 900 “blue” What the witness would report 100 “green” 5 “blue” 45 “green” “green” answers are more often wrong than right! (100/145 are wrong) In this case, the base rate information overwhelms the diagnostic information.

Base rate neglect has real world consequences... Suppose mammograms are 85% likely to detect breast cancer, if it’s really there (hit rate), and 90% likely to return a negative result if there is no breast cancer (correct rejection rate). Suppose we are testing a patient population with an overall likelihood of cancer of 1%. If the mammogram detects cancer, what are the odds that the patient really has cancer?

Mammogram Indicates CancerNo Cancer Total cancer present ,000 cancer absent 9,900 89,100 99,000 In this case, when the mammogram indicates the presence of cancer, there is an 850/10,750 likelihood that the patient actually has cancer (only about an 8% chance). While positive results on a mammogram surely indicate that more tests would be wise…they should be viewed in the context of the overall probability of the disease they are testing for. Studies have shown that doctors have the same base rate neglect tendencies as the rest of the population. What’s really there

The Availability Heuristic: Examples Which household chores do you do more frequently than your partner? (e.g. washing dishes, taking out the trash, etc.) - wives report 16/20 chores - husbands report 16/20 chores Ross and Sicoly (1979) Why? Availability! - I remember lots of instances of taking out the trash, washing dishes, but I do not remember lots of instance of my wife doing it

The Availability Heuristic: Examples Which is more frequent? Words that begin with “R”, or words with “R” as their third letter? Why? Availability! - I can come up with many examples of ‘R_ _ _’, but few of ‘_ _ R_’

The Availability Heuristic Tendency to form a judgment on the basis of information is readily brought to mind. Why is it useful? - Frequent events are easily brought to mind ( words that start with X ) Why is it sometimes misleading? - Factors other than frequency can affect ease of remembering: --Ease of Retrieval (the “r” example) --Recency of the example (advertisement, news) -- Familiarity (“what % of people go to college?”)

Testing the Availability Heuristic - Keep frequency invariant - Experimentally manipulate availability - Measure estimated frequency (dependent variable) Subjects read a list of names - 50% of names are male names, the rest are female - Group A: Some male names famous (Bill Clinton) - Group B: Some female names famous Test: Where there more men or women in the list?

Anchoring Tendency to reach an estimate by beginning with an initial guess and altering it based on new information. In general –People rely too heavily on the anchor (initial value) –Adjustments are too small –even when the anchor (reference point) is known to be uninformative.

Anchoring: Example “What is the proportion of African nations in the UN? Answer: ‘45%’ “65” “10” “What is the proportion of African nations in the UN? Answer: ‘25%’