MAR 6591 Final Exam Questions & Answers 2024/2025
The difference between normative, descriptive, and prescriptive approaches to studying judgment and decision making - ANSWERSNormative· how should people make decisions
o Rational, optimal
o Norms of good practice
o Good. Bad
Descriptive...
The difference between normative, descriptive, and prescriptive approaches to studying judgment and
decision making - ANSWERSNormative· 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 - ANSWERS· Uncontrolled
· Effortless
· Associative
· Fast
· "Gut Reaction
Reflective System 2 - ANSWERS· Controlled
· Effortful
· Deductive
· Slow
· "Conscious Thought"
, availability heuristic - ANSWERSEstimate 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 - 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 - 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 - 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 - 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)
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