Judgments and Decisions

Psych 253

Judgments/Decisions Normative Theories

• Risky Choices• Repeated Decisions

with Ambiguity• Probabilities• Evaluations• Predictions

Judgments/Decisions Descriptive Heuristics/Theories

• Risky Choices• Repeated Decisions

with Ambiguity• Probabilities• Evaluations• Predictions

Judgments/Decisions Prescriptive Lessons

• Risky Choices• Repeated Decisions

with Ambiguity• Probabilities• Evaluations• Predictions

Impediments to Good Decision Making

• Missing information

• Confounded information

• Side effects (treatment effects)

• Confusing information

• Unused information

Missing Information

Consider a new decision rule for admitting students to medical school

Performance

Successful

Unsuccessful

Selection Policy

AdmitReject

SuccessfulAdmits

UnsuccessfulAdmits

SuccessfulRejects

UnsuccessfulRejects

Confounded Information

Now add a new training programStudents in the medical school have a 50%

chance of success, and the training program improves the success rate to 80%. Why?

1. A superb selection rule and a worthless training program

2. A superb training program and a worthless selection rule

3. Some combination of both

Side effects (sometimes called treatment effects)--effects that influence an outcome and occur after an intervention or judgment

is made

Hawthorne EffectDemand Effects

Confusing information

When evaluating our decisions, we usually lack the information to assess the consequences which means the information is confusing.

What if we had moved to another city, not married, not chosen a career or taken a job? The most important decisions we make tend to be fairly unique and provide little opportunity for learning.

Unused information

Classic example is the Space Shuttle Challenger. If the temperatures for incidents that did not occur had been included with the temperatures for incidents that occurred, a pattern would have been easy to see.

What is required to learn predictive relationships?

• Feedback is necessary but not sufficient. Accurate and immediate feedback is rarely available in the real world.

• Arranging feedback to detect correlations (and test hypotheses). Need to group all A cases together, all not A cases together, etc.

• Being cautious about inferences. Even with that information, causal variables many go in the opposite direction of observed correlations.

What heuristic applies?

__________________Your estimate of the probability of a shark attack off the California coast sharply increases after you read about a shark attack in the newspaper.

What heuristic applies?

________________ You or your spouse is 25

years old and pregnant. The doctor does an

amniocentisis test to check for birth defects. The

test comes back positive for Down's syndrome

(mental retardation). You know the chances of

this occurring in the population among women

who are 25 years old is 1 in 1000, but it still

seems like a certainty.

What heuristic applies?

___________________ You expect an athlete

who did extremely well last year to do just as well

this coming year.

What heuristic applies?

___________________ You have a friend who applies for a high-powered job. You hope he gets it, and you cross your fingers. The following week your friend calls and tells you he got the job. You tell yourself that you knew he would get it all along.

What heuristic applies?

___________________ You believe coffee drinkers are more likely to be smokers and you do a survey to find out how strong the association really is. You hardly remember the smokers you interviewed who were not coffee drinkers, but you clearly recall every one of the smokers who drank coffee.

What heuristic applies?

__________________ You are the chief legal counsel for a firm that has been threatened with a huge lawsuit. The firm will go bankrupt if it losses. You are almost certain that the firm will win, so sure in fact that you reject an out-of-court settlement.

What heuristic applies?

_________________ You hired a research assistant to

work for you. You expected excellent performance,

but early evidence suggest the assistant is not doing well.

You spent a fair amount training her, and it may be

that she is just having trouble “learning the ropes”.

You decide to wait a bit longer. Two months later, her

performance is still weak. Nevertheless, you decide

again to keep her, and you tell yourself that she will

surely improve.

What heuristic applies?

__________________ Sally did poorly on her exam. She learns that Joan did well. Sally tells herself that the timing on the exam was all wrong. She had 2 other exams the day before and there was no time to study for the 3rd exam. But Joan had the same 3 exams. So why did Joan do well? Sally tells herself that Joan must really be smart.

What heuristic applies?

___________________A real estate agent comes over talk to you about how to sell your house. She asks you, "What is your asking price?". You have a range of possible answers, and you respond by telling her your highest value.

Decision problem 1

• A doctor wants to build a decision aid to help detect prostate cancer in his patients. He thinks the patient’s age, PSA count (the result of a blood test), and biopsy results can predict cancer. What should he do?

Decision problem 2

• A firm wants to develop a model to identify teenagers who might behave violently. What should they do?

Decision problem 3

• You are asked to help the Philadelphia police department improve their hiring policies. What do you do?

When making risky choices…

Remember EU and Decision Trees

You leased some offshore load that may have oil. You must decide whether to drill for oil or abandon the lease. A geologist estimates a 40% chance that the land has oil. Drilling will cost $400,000 and you will find out if there is oil. If you drill and find oil, you will get $1 million. If you drill and find no oil you will recover nothing.

What strategy maximizes expected net profit? What is it worth to you to do tests before drilling?

When making repeated decision with ambiguous information….

Remember Signal Detection Theory—a framework for thinking about the probabilities and costs of both errors

CR FA

HITMISSSignal

Noise

“Noise” “Signal”

When assessing the probability of an event…

Remember Bayes Rule

5 patients out of 1000 have a particular form of cancer. There is a test to detect the disease. The test result is positive in 95 out of 100 patients with cancer, and the test result is negative in 95 of 100 patients without cancer.

If a test is given to a randomly selected person from the population and the test result is positive, what is the probability the patient has cancer?

When evaluating multi-attribute options….

Remember Multi-attribute Utility Theory• Suppose you are trying to decide which

graduate school to attend. You have collected information and visited all of them. Now what?

Put the information in a table.

Interest Quality Faculty Cost Benefits

School 1 3.5 3   2 9 3

School 2 4 3   5 5 4

School 3 2.9 5   8 6 6

School 4 3.1 2   1 6 2

When predicting future events….

Remember regression and use statistical models at a minimum to check yourself

An editor of a publishing company reviews a manuscript and is favorably impressed. He tells the author, “The book reads like a best-seller. Among novels of this type that were published in recent years, I would say that only 5% impressed me more.” What is the editor’s estimate of book sales?Most editors would forget to regress due to the unpredictability of the event.

Good decisions involve some apparent contractions.

Good decision makers use methods/tools that take advantage of human strengths and minimize human weaknesses.

Good decisions say something important about who we are.