decision making and reasoning Flashcards
decision making
when we make decisions or judgments, we use heuristics guided by the principles of what we expect
psychological theory
framing of information as well as emotions can guide how we asses risk when we make choices - ie prospect theory
neuroscience
activity in emotional areas of the brain (amygdala) are linked to framing effects and prospect theory
loss aversion and amygdala processing (de martino et al, 2010)
people avoid gambles (choices) when they are equally likely to either lose a small amount $10 or win a larger amount $15
patients with bilateral amygdala lesions lack loss aversion on gambling tasks compared to healthy controls
suggests that amygdala plays a key role in loss aversion
neuroeconomics
studying how we make decisions, formalizing theories and linking it to the development of the brain
- combo of economic theory, neuroscience and psychology
reasoning
a thought process that brings an individual to a conclusion
guides decision making
inductive reasoning
making general conclusions from specific observations (specific to general)
conclusions can be false - when we are unaware of inductive reasoning, it can become a heuristic
a “probably but not definitely true” type of reasoning
importance of inductive reasoning
basis of much of human learning
applying learned rules to new situations
language learning - learning the meaning of balloon when you see “purple balloon dog” when you already know ‘purple’ and ‘dog’
deductive reasoning
using general theories to reason about specific observations (general to specific)
logic
deductive reasoning: formal systems for generating statements that will be true if rules of the system are followed
syllogisms
deductive reasoning problems that involve two premises and a conclusion
validity of syllogisms
is the conclusion true given the premises’ logical form
valid = logical rules, not truth
ex. valid structure
(all A are B, all B and C, therefore, all A are C)
atmosphere effect
people rate a conclusion as valid when the qualifying words in the premise match those in the conclusion
mental model theory
people construct mental simulations of the world based on statements to judge logic and validity
why we fall for negative statements - hard to imagine the absence of something
omission bias
idea that withholding is not as bad as doing
- inaction is harder to classify as wrong than action
another reason why people have trouble reasoning with negative action
belief bias and syllogisms
people have problems reasoning with syllogisms in which logical validity conflicts with truth
the content of a syllogism can lead to errors due to belief bias - the tendency to think a syllogism is valid if the conclusions are believable
more dominant for invalid syllogisms
- when a conclusion is believable, people are much less likely to question its logic, whereas when a conclusion is unbelievable, it is much harder for people to accept, even when the logic is sound
conditional reasoning
“if p then q” statements where p is the antecedent and q is the consequence
watson’s four card test
ps shown 4 cards and given an if p then q statement
ex. if a card has a vowel has a vowel on one side, then it has an even number on the other side, which two cards should you flip?
E, F, 2 or 5
lots of people don’t test correctly - instead, rely on confirmation bias (tendency to seek out information that confirms what you believe)
instead, have to rely on falsification principles
falsification principle
you need to look for situations that would falsify a rule
rule to solve if P then q
- choose the P card and the not Q card
familiarity effects
people do better on the watson four card task on familiar topics
example:
if a person is drinking a beer (P), then the person is over 21 years old
many more people can solve this task than the more abstract version
when do biases occur
when heuristics are over applied
systematically inaccurate choices that don’t reflect a current situation
three categories of heuristics
ones that:
- bias how we interpret info
- bias how we judge frequency
- bias how we make predictions
representativeness bias
probability that an item (person, object, event) is a member of a category because it resembles thay category
related to over use of schemas, and other preexisting knowledge structures
stereotyping, base rate neglect, and conjunction fallacy
base rate neglect
we ignore important rate information when reasoning
