Transcript Common Biases Chapter 2

Common Biases Chapter 2
13 Specific Biases bases upon
availability heuristics
Bias 1: Ease of Recall
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Vividness & recency
Problem 3
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Tobacco - 435,000
Poor diet – 400,000
Motor vehicle – 43,000
Firearms – 29,000
Illicit drugs – 17,000
Bias 1: Reason
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Since there is some much press about
drug and firearm death we assume a
large amount of deaths per year.
Bias 2: Retrivevability
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Based upon memory structures
Answer 4b would include both ing
words and any word with the letter n in
the seven place, therefore 4b should
the same or even slightly more
The human mind “sees” many words
ending in ing you automatically assume
4a to be higher
Bias 3: Presumed Associations
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Chapman & Chapman (as cited by
Bazerman, 2006) have noted that when
the probability of two events cooccurring is judged by the availability of
perceived co-occurring instances in our
minds, we usually assign an
inappropriately high probability that the
two events will co occur again (p. 21).
Bias 3
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Examples?
Summary
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Ease of recall, retrievability, and
presumed associations indicate the
misuse of availability heuristic
A lifetime of experience in general allow
us to recall more likely events and
frequent events
Bias 4: Insensitivity to Base
Rates
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Problem 5?
Judgmental biases of this type frequently
occur when individuals cognitively ask the
wrong question
Peter Drucker (2005) the greatest source of
mistakes in top management is to ask the
same questions most people ask (n.p.)
“What needs to be done?” should be your
question
Bias 5: Insensitivity to Sample
Size
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Problem 6?
The small hospital!
Sampling theory, it is easier to 6 heads with
10 flips of a coin than 6,000 heads with
10,000 flips of a coin
Sizable sample much better in marketing
research, but 4 out of 5 dentists surveyed
recommend sugarless gum!
Bias 6: Misconceptions of
Chance
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Problem 7?
Is the performance of the sixth stock
related to the first five?
The hot hand belief (pp. 24)
The “law of small numbers” (pp. 25)
Bias 7: Regression to the
Mean
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Problem 8?
Read the two examples on page 27;
Flight instructors comments and
management comments.
Bias 8: The Conjunction
Fallacy
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Problem 9?
Look at your rankings of C,H,F
Did you place H before F?
Simple Statistics demonstrate that a
conjunction cannot be more probable that
any one of its descriptors, but will usually
judged more probable than a single
component descriptors
Most “feel” the conjunction is more
representative than the component
Representativeness Heuristic
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Experience has taught us that the likelihood
of a specific occurrence is related to the
likelihood of a group of occurrences which
that specific occurrence represents
Insensitivity to base rates, insensitivity to
sample size, misconceptions of chance,
regression to the mean, and the conjunction
fallacy
Lets go beyond availability and
representativeness
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Problem 9?
Irrelevant anchors
Anchors gives some info however
incorrect it may be & there is probably
some commonalities, right?
Roulette wheel & African countries in
the UN
Bias Conjunctive & Disjunctive
Events Bias
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Problem 10?
BAC
C-52%, A-50%, & B-48%
C & B are complements of each other
According to Tversky & Kahneman (as cited
by Bazerman, 2006) “even when the
likelihood of failure in each component is
slight, the probability of an overall failure can
be high if many components are involved” (p.
32).
Overconfidence
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Problem 12?
Overconfident when responding to
questions of moderate to extreme
difficulty
Imperfectly estimate their own
performance?
Bias 12: The Confirmation
Trap
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2-4-6 rule – It is easier to find “see” the
information backing up a decision than the
bad information.
Yes person & Devils advocate consulting
firms. “Our desire to confirm our initial ideas
is so strong that we will pay people to back
us up!” (Bazerman, 2006, p. 36).
“A willingness to attempt to falsify
hypotheses, and thus to test those institutive
ideas that so often carry the feeling of
certitude” (Watson, 1960, pp. 139)
Bias 13: Hindsight and the
curse of knowledge
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The hindsight bias (Fischhoff, 1975)
Curse of Knowledge