Concepts and Reasoning

Question 1

concept

Answer 1

mental representations of individuals and categories

Question 2

Classical categories

Answer 2

(aka Aristotelian) a list of properties that are necessary and sufficient conditions to define members of a category

Question 3

Family Resemblance Categories

Answer 3

NO common properties , and instead different properties shared by different subsets

Question 4

Normative Models of Reasoning

Answer 4

How people SHOULD think: logic(deductive), probability theory(inductive)

Question 5

Descriptive models of Reasoning

Answer 5

How people DO think

Question 6

Deductive Reasoning

Answer 6

general to specific
certain
Ex.:
Socrates is a man
All men are mortal
Socrates is mortal

Question 7

Inductive Reasoning

Answer 7

Specific to general
probabilistic
Ex: 
Socrates, Plato, and Aristotle are men
Socrates is mortal
Plato is mortal 
Aristotle is mortal
All men are mortal.

Question 8

Fallacies in Deductive Reasoning

Answer 8

confirmation bias: people seek evidence to confirm, not falsify their hypothesis
Content Effect

Question 9

Fallacies in Inductive Reasoning

Answer 9

misconceptions of Randomness
misconceptions of risk
misperception of how data supports hypotheses

Question 10

The Content Effect

Answer 10

people are good logicians when it comes to particular kinds of content

Question 11

Frequentist probability

Answer 11

What proportion of events have a given outcome in the long run?
(people tend to use good intuitive statistics)

Question 12

Subjectivist Probability

Answer 12

How confident are in the outcome of a single event?

people tend to use memory, stereotypes, judgment, etc.

Question 13

prototype

Answer 13

combination of the most common shared properties among members of a family resemblance category
usually does not actually exist in reality

Question 14

Gambler’s Fallacy

Answer 14

Fallacy: randomness is a causal process. it compensates for deviations from expected pattern.
Reality; Randomness dilutes the deviations

Question 15

Availability Heuristic

Answer 15

the easier to imagine an example, the more likely an event is estimated to be

Question 16

p(H|D)

Answer 16

probability of the hypothesis given the data

Question 17

p(H)

Answer 17

prior probability of the hypothesis

Question 18

p(D|H)

Answer 18

likelihood of the data given the hypothesis

Question 19

p(D)

Answer 19

probability of the data

Question 20

Bayes’ Theorem

Answer 20

[P(H) X P(D|H)]
P(H|D) =__________
P(D)

Question 21

base-rate neglect

Answer 21

If presented with related base rate information (i.e. generic, general information) and specific information (information only pertaining to a certain case), the mind tends to ignore the former and focus on the latter.

Question 22

Representativeness heuristic

Answer 22

the more typical an observation is of a hypothesis, the more likely the hypothesis seems