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Reasoning Notes

by: Krista Lindenberg

Reasoning Notes PSY-4073-5073-001

Krista Lindenberg
Arkansas Tech University
GPA 3.8

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About this Document

These notes cover topics from lecture on Monday, April 11.
Cognitive Psychology
Steven Andrew Berg
Class Notes
25 ?




Popular in Cognitive Psychology

Popular in Psychlogy

This 3 page Class Notes was uploaded by Krista Lindenberg on Monday April 11, 2016. The Class Notes belongs to PSY-4073-5073-001 at Arkansas Tech University taught by Steven Andrew Berg in Winter 2016. Since its upload, it has received 20 views. For similar materials see Cognitive Psychology in Psychlogy at Arkansas Tech University.

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Date Created: 04/11/16
Cognitive Psychology Week of April 11, 2016 Reasoning  Judgment o We make basic decisions about things such as  Will m flight depart on time  Am I more likely to die by car or plane o Answers in response are often wrong o Humans use probabilities and statistical info (not always consistently or logically) o We tend to exploit two heuristics  Availability  Representative  Availability o Refers to frequency of information that is a central in drawing conclusions o Particularly useful in making predictions o Core element in reasoning by induction  Availability Heuristic (Glenlivet & Kahneman, 1973) o Sample memory, use the info retrieved as an indicator of frequency o Easier to think of examples of the event after seeing many related stories o Ex. After seeing many news stories of home foreclosures Ps may predict it to happen more often than it actually does o Good heuristic when accessible memory is a non biased sample, but that is atypical.  Availability Heuristic o Overestimation of event likelihood is a major pitfall of the heuristic  Rare events are more memorable  Recency of the event influences the ease of retrieval from memory.  You are only exposed to certain events, like the news you watch or the books you read o Anchoring refers to the observation that people will use any available info as a reference for making decisions  Anchoring o Tversky and Kahneman (1973)  Asked Ps the % of counties in the UN that are from Africa (35%)  A wheel with #1-100 was spun  When stopped, Ps asked if estimates was > or < #  Then they gave their actual estimate  This was no ordinary wheel though, it was rigged to stop @ 10 or 65  When stopped at 10, people estimated 25%  When stopped at 65, people estimated 45%  P’s anchored their estimates based on the wheel, which had nothing to do with the question at hand  Summary of Availability Heuristic o Ps make judgments involving frequency info based on whatever they find in memory o Ps have difficulties correcting deficiencies  Representative Heuristic o Members of a category share traits o We attribute category properties to the instance that is novel o If an item is highly similar to the typical members of a category then category membership is easily determined o This is a good strategy when…  Groups are fairly homogenous  Low variability of features among members  Category overlap is low  Category distinction from other categories  Boundary between categories is broad o Commonly leads to error when:  Reasoning from a population to an instance  I toss a fair coin 6 times; it is heads all 6 times  On the 7 toss, is heads or tails more likely?  If Ps respond more likely to be tails, this is the gambler’s fallacy (something’s got to give, my luck is about to run out, etc)  Reasoning from an instance to a population  Hamill et al. had Ps watch a video of a prison guard being either compassionate or contemptuous o Control group was told nothing o Group 2 was told that the guard’s behavior was atypical o Group 3 was told that the guard’s behavior was normal  Reports were still consistent with what they saw in video; they disregarded what they were told  Am I more likely to die in a plane crash or in a car crash?  If you said plane, then you are neglecting base rates. There are many more car accident deaths per lifetime than plane crashes.  When diagnostic info is present, people tend to use it and ignore base rates  Optimal decision uses both base rates and cues from the environment  Base rates  Varies with 3 factors o Expectation that chance plays a role in the events o Whether or not the info highlights the use of sampling so observers understand that the data is a sample o Background beliefs about the homogeneity or heterogeneity of opinion sets


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