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The difference between normative, descriptive, and prescriptive approaches to studying judgment and decision making correct answers Normative· how should people make decisions o Rational, optimal o Norms of good practice o Good. Bad Descriptive: · how do ppl make decisions o Behavioral, li...

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MAR 6591 Final Exam || Questions and 100% Verified
Answers.
The difference between normative, descriptive, and prescriptive approaches to studying
judgment and decision making correct answers Normative· how should people make decisions
o Rational, optimal
o Norms of good practice
o Good. Bad

Descriptive: · how do ppl make decisions
o Behavioral, limited cognitive capacity
o Just the facts
o Psychological

Prescriptive:· how can we improve decision making
o Corrective measures, debiasing

Automatic System 1 correct answers · Uncontrolled
· Effortless
· Associative
· Fast
· "Gut Reaction

Reflective System 2 correct answers · Controlled
· Effortful
· Deductive
· Slow
· "Conscious Thought"

availability heuristic correct answers Estimate the likelihood or frequency of an event based on
the ease by which examples come to mind
Example: do people die more from car accidents or colon cancer?

Representativeness correct answers · Judge likelihood based on similarity/ matching
· Are more people in the US killed or by bears?
· How things are labeled affect judgement

Anchoring and adjustments correct answers · Use convenient value as a starting point in
numerical assessments. Adjustments away from the anchor are typically too small
· Works when there is uncertainty about a number
Adjustments away from the anchor are typically too small.
Example: Red cross example

Prediction by evaluation correct answers -when you make a prediction, you fall back on the
evaluation you have

, -using past evaluations for future predictions will intuitively give you similar responses.
-People predict by evaluation and the predictions are non-regressive.
Example: GPA predicting how well a student will do

Normative rule for numerical prediction correct answers -Predictions should be regressive
relative to evaluations
(i.e., predictions should be less extreme than evaluations).
-Regress toward the mean based on strength of the relationship:
-Weaker correlations
regress more (stay closer to mean)
-Higher correlations can predict further away from the mean

Totally uninformative (r = 0)
Prediction=average
Totally informative (r = 1) Prediction=evaluation

Descriptive summary for numerical prediction correct answers -People predict by evaluation &
are thus non-regressive
-An instance of reliance on representativeness heuristic

Bayes Rule and Base rate neglect correct answers Learn chart!!

Base rate neglect: not accounting for the base rate, but "[B]ase rates matter, even in the presence
of evidence about the case at hand."

Overconfidence in intuitive judgement correct answers Expert game:
overconfidence in knowledge, when the expert was chosen and got it wrong

Overconfidence for individuals: setting too-narrow intervals

Alternatives, Beliefs, and Consequences of decisions correct answers Your chosen alternative
and uncertain events jointly define what outcome you get

Using the chart with Event and probability, then alternatives

Aunt Judy $200

Expected value as a way of valuing alternatives under conditions of uncertainty correct answers
the average of each possible outcome of a future event, weighted by its probability of occurring

-Expected value Is not the only way to make rational decisions because we must also factor in
utility
Example of why it's not always rational: St. Petersburg paradox
(If first H on 3rd flip, $8)

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