PSYC 2650 Lecture Notes - Confirmation Bias, Fair Coin, Rorschach Test

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Chapter 12: Judgment: Drawing Conclusions From Evidence
-we draw conclusions from out experiences
-the focus of this chapter will be on Induction - a process in which you try to go beyond
the available information,
-we will want to compare a Descriptive Account of human induction telling us how the
process ordinarily proceeds, with a Normative Account, how things ought to go
-in this way, we will be able to ask whether our day-to-day judgments are foolish or sen-
sible and whether our commonsense conclusions are justified or not
Judgment Heuristics
-experiences can be an extraordinary teacher
-the process of education doesn’t depend just on the teacher, it also depends on the
student
-the capacity to learn depends on the person who has the experience and their memory
-virtually any factor that influences memory will influence the pattern of conclusions and
the quality of our judgments
-we often draw conclusions based on experiences and memories gathered over months
and years, if these memories are selective, incomplete or distorted then the validity of
the conclusions is questionable
Attribute Substitution
-attribute substation is a strategy when you’re trying to evaluate some point but don’t
have easy access to the target information, you therefore rely instead on some other as-
pect of experience that’s more accessible and that is a plausible substitute for the infor-
mation you seek
-e.g. trying to predict how well you will do in a course next semester do you ask how
your friends have done, how many have done well, how many haven’t done well
-in this case you are seeking information about frequencies - assessments of how often
various events have happened in the past
-you may not be able to recall all of the friends that have taken the course and their ex-
act grades so you do a quick scan through memory for relevant cases
-if you remember 4 friends with good grades, you’ll conclude this is frequent
-you are relying on availability - the ease with which things come to mind, as an index
for frequency
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Availability Heuristic - the reliance on availability as a substitute for frequency
-a different example is if you are trying to judge if your friend is lying, you could try to re-
member everything you know about your friend and everything you know about liars
Representativeness Heuristic - using resemblance in place of information about cate-
gory membership
The Availability Heuristic
-heuristics are reasonably efficient strategies that usually lead us to the right answers
-they allow errors in order to gain efficiency
-to avoid errors, you need a slower and effortful strategy
The Wide Range of Availability Effects
-people regularly overestimate the frequency of events that are quite rare
-e.g. buying lottery tickets
-events that are unusual are likely to catch your attention, you notice them ensuring
they are well recorded in memory
-in a study, participants are asked to recall 6 or 12 examples of themselves being as-
sertive, those in the 6 group believed they were assertive people because it was easy to
come up with examples, those in the 12 group thought the opposite
-participants who recalled more examples had more evidence of their assertiveness
-it’s not the quantity of evidence that matters, it’s the ease of coming up with examples
-availability can also be influenced by many other factors
-imagine you are asked to vote how much money the government should spend on re-
search projects all aimed at saving lives
-people assert that motor vehicle accidents and homicide are more frequent then stom-
ach cancer so they vote for those even though that is untrue
-people are heavily influenced by the pattern of media coverage
The Representativeness Heuristic
-this amounts to an assumption that the categories we encounter are relatively homo-
geneous
-that leads us to act as if each member of a category is “representative” of the category
-e.g. if someone is a lawyer you give them a stereotype and expect them to hair traits
associated with lawyers, also if someone looks like a lawyer and has lawyer traits, we
conclude they are a lawyer
-this leaves us quite willing to draw conclusions from a relatively small sample
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-these reasoning patterns often lead us to correct conclusions because many cate-
gories are homogeneous
-there can be error of course
Reasoning From the Population to an Instance
-gambler’s fallacy - if a coin has come up tails 6 times in a row, it is more likely to be
heads on the next toss
-the “logic” leading to this fallacy seems to be that is the coin is fair, then a series of
tosses should contain equal numbers of heads and tails
-the coin is “overdue” for heads to bring out balance
-the explanations for this lies in our assumption of category homogeneity
-we know that over the long haul a fair coin will produce equal numbers of heads and
tails
-we expect any “representative” of the category with show a 50-50 splits
Reasoning From a Single Case to the Entire Population
-people expect each subset of the category and each individual within the category to
have the properties of the category overall
-people also expect the overall category to have the properties of the individuals so
they are willing to extrapolate from a few instances to the entire set
-you regularly hear “man who” or “woman who” arguments”
-e.g. don’t by that brand of car, I know a man whose broke down last week
-e.g. what do you mean cigarette smoking causes cancer? I have an aunt who smoked
for 50 years and she runs marathons!
-we are willing to take that as seriously as a larger sample
Anchoring
-we use shortcuts in a wide range of settings including ones with important stakes
-anchoring - often we don’t know the answer to a particular question, but we do have an
idea about what “ballpark” the answer is in so we use that as an anchor and reach our
answer by making some suitable adjustment to that anchor
-the problem is we usually adjust too little so we are more influenced by the initial an-
chor than we should be
-e.g. asked if Ghandi lived past 50 and then asked to guess his age (average guess
was 67), others asked if Ghandi lived past 9 and then asked to guess his age and
guessed much lower because the anchor was lower
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