5. Human Reasoning

Question 1

Reasoning:

Answer 1

cognitive process in which conclusions are elaborated or evaluated from previous information (premises)

Allows us to make decisions and solve problems

Question 2

Types of reasoning:
Formal reasoning

Answer 2

premises are given and impossible to modify and theres only one possible conclusion that is produced through deductive steps

Question 3

Types of reasoning:
Informal reasoning

Answer 3

premises can be revised or modified and several argumental lines are produced leading to different conclusions

Question 4

Types of reasoning:
Deductive reasoning

Answer 4

• Start with premise
• leads to certain conclusion
• Either valid or invalid
• aim to test hypothesis
• use of formal logic

seen in natural sciences

Question 5

Types of reasoning:
Inductive reasoning

Answer 5

• Make repeated observations
• Generalization process
• wide range of probability, inferences can be on a continuum
• aim to create new theory from existing data
• use of informal logic

seen in courtrooms, media

Question 6

How do we do inferences?

Answer 6

Hypothetico-deductive: theory - experiment - results - observations and contexts

Inductive: observations and context - theory

Question 7

Prediction and probability

Why do we calculate it

Answer 7

to solve problems and make decisions. It is influenced by character, age, gender, mood, trend to optimism or pessimism

Quite good at calculating easy events probabilities, we usually dont apply probability knowledge (eg statistics), but heuristics

Question 8

Prediction and probability

Problem-solving

Answer 8

Algorithms: methodological, exhaust all probabilities before arriving to solution (time-consuming, guaranteed solution)

Heuristics: simple thinking strategies, allow us to make judgements efficiently
(less time-consuming, more error-prone)

Question 9

Heuristics (Tversky and Kahneman)

Availability heuristics

Answer 9

making a decision based on how well we can recall or how frequently something occurs

Question 10

Heuristics (Tversky and Kahneman)

Representative heuristics

Answer 10

decision based on mental models of stereotypes

probability that it will match our expectations,

Question 11

Heuristics (Tversky and Kahneman)

Affect

Answer 11

judgement of life happiness is lower if it comes after the question of love life than if it is asked alone

Question 12

Heuristics (Tversky and Kahneman)

Anchoring and asjustment

Answer 12

estimates are made by starting from an initial value (anchor) and adjusting to yield a final answer)

Question 13

In representative heuristics, what are the classical judgement errors

Answer 13

• Conjunction fallacy: judging that 2 events are more probable than 1 of them
• Misperceiving randomness (Gambler’s fallacy): belief that small samples reflect the population they are drawn from
• Insensitivity to sample size: judge the probability of obtaining a sample statistic without respect to the same sample. Variation is more likely in small samples

Question 14

Heuristics (Tversky and Kahneman)

Systematic error and inferential biases

Answer 14

• expose our intellectual limitations
• reveal psychological processes that govern judgement and inference
• help mapping of intuitions by indicating which principles of statistics or logic are non-intuitive

Question 15

What is maximization in decision making?

Answer 15

it involves choosing the best option after checking all of them
when you just choose one that is “good enough” its called satisficing

Question 16

Heuristics (Tversky and Kahneman)

3 separated programs of research

Answer 16

• Heuristics we use and biases we are prone to, using tasks of judgement under uncertainty, including predictions and evaluations of evidence
• Prospect theory: model of choice under risk and with loss aversion in risk-less choice
• Framing effect: implications for rational-agent models

Question 17

Causality and causal analyses biases

Answer 17

• illusion of control (world as predictable and controllable)
• similarity (representative heuristic)
• fundamental attribution error (undervaluing situational factors and attributing actor features as a causal agent)
• Self and others attribution (internal for others, external for me)
• Minimum causality (overestimation of a single cause attribution, in a chain we can overweigh the first event)