Quiz 4 Flashcards
judgment
the process through which people draw conclusions from the evidence they encounter
evidence
sometimes loosely defined- could be good or bad
frequency estimate
estimate of the frequency of the event
Example: What is the frequency of a monster in a room?
Attribute substitution
we make a decision about frequencies without using frequency estimate as evidence
we rely on easily assessed information to make a judgement- substituting information
attribution substitutions
often rely on information obtained through heuristics: efficient strategies that usually lead to the correct answer
types of heuristics
availability heuristic
representativeness heuristic
affect heuristic
effort heuristic
availability heuristic
the ease with which examples come to mind is a proxy for frequency or likelihood
- asked whether it is going to rain tomorrow, you are going to think about if it rained a lot today, which is used as a proxy
- who do you listen to the most? you list the one you were just listening to
heuristic errors
-are there more car or plane crashes- if plane crashes happen you hear it all over the news, but there are more car accidents
-are there more words with s in 1 or 3 position, you will choose 1 because it is not readily available, when in fact there are more with s in the 3rd position
ease of remembering events impacts judgment
Schwarts et al. (1991) study on assertiveness
- remembering 5 is easy, remembering 10 is more difficult, people that came up with more had to think harder, so they felt they were not very assertive, the group that had to think of five, the ease of recalling them made them feel assertive
why do we overestimate the frequency of rare events?
Rare events are more notable, we will remember them
representative heuristic
assumption that resemblance to the prototype reflects the probability
-often relies on the assumption of homogeneity
is this man on the train more likely to be a professor or farmer?
you think, professor, but realistically, there are around 50,000 professors and 262,000 farmers in Canada; based on statistics, he is more likely to be a farmer. the information isnt informative, but rely on visuals about him looking like a professor.
categories
when you learn someones category, you usually assume a lot about them. it leads to incorrect stereotypes
“man who” arguments
someone who knows someone who did something, it is prevalent.
a smoker who ran a marathon- they are an exception
“gambler’s fallacy”
the coin is tails for 11; you have to bet what the next flip is going to be; people will say heads because there have already been so many tails, not recognizing that it is an independent event, so the events before don’t impact it. we think there is an effect there.
covariation
x and y (2 events) “covary” if the presence (or magnitude) of X can be predicted by the presence (or magnitude) of Y, and vice versa
positive example of covariation
age and year/level in university- typically the older you are the higher year/level you are.
negative example of covariation
exercise and risk of heart attacks- the more you exercise, the less likely you are to have a heart attack
covariations and causation
often, covariations are incorrectly assumed, and causal claims are improperly made
example of covariations and causation
astrology and personality- people that are libra have these personality traits- you think you know alot about them because of their zodiac symbol
confirmation bias
tendency to be more alert to evidence that confirms one’s beliefs than to evidence that challenges them
example of confirmation bias
your friend is a libra, so you focus more on their personality traits that align with libras, confirming your own bias/conclusions, leaving out the traits that are like the other zodiac signs
you fear dogs, so you pay attention to the vicious dogs, making them more available, reconfirming your belief, not paying attention to the adorable, gentle ones
base- rate information
information about how frequently something generally occurs
diagnostic information
does an individual case belong to a category
Kahneman and Tversky (1973)
told participants there are 70 lawyers and 30 engineers in a group. given this description, which group does someone who “likes carpentry, sailing, math puzzles; dislikes politics” belong to?
- closer to prototype of engineer, when in reality, many lawyers have these likes and dislikes, the most informative thing is how frequently these things happen
base rates use
we can and do use base rates well when base rates are all we have, but when diagnostic information is also given, people neglect the base rate
base rates: conjunction fallacy
the false assumption that a combination of conditions is more likely than either condition by itself
probability of A will always be higher than the probability of A and B.
why do we use a heurisitc if they keep misleading us?
they usually work, are efficient, they are good
secondary thinking system
another path, we can engage to answer more complex, effort-requiring questions
dual process model
type 1: fast and automatic thinking
vs.
type 2: slower, effortful thinking
type 1
reliance on heuristics
base rate neglect affected by type of data
emphasizing randomness
type 2
more likely to be correct
education encourages
the cognitive reflection test
assesses individuals’ ability to suppress an intuitive and spontaneous (type 1) wrong answer in favour of a reflective and deliberative (type 2) correct answer
types of reasoning
induction and deduction
induction
process through which you forecast about new cases based on observed cases
deduction
process through which you start with “givens” and ask what follows these premises
confirmation bias
a greater sensitivity to confirming evidence and a tendency to neglect disconfirming evidence
example of confirmation bias
participants given three numbers (2,4,6) and tasked with figuring out the rule.
test new trios to determine the rule (8,10,12) or does the number just have to be higher than the previous (7,8,9)
result of confirmation bias
participants generally only sought to confirm the rules they were proposing
disconfirming evidence
information inconsistent with one’s belief is often scrutinized for flaws
example of disconfirming evidence
Gamblers believe their strategy was good but the loss was a ‘fluke’ or ‘coincidence’
belief perseverance
tendency to maintain belief even when given undeniable disconfirming evidence
logic
confirmation bias suggests a failure to be logical
can demonstrate using categorical syllogisms and conditional statements
