Hypothesis Testing and Bias

Reasoning and Hypothesis Testing

• Confirmation bias is the tendency to seek out and favor information that confirms existing beliefs or hypotheses.
• Falsification is the attempt to disprove a hypothesis through experimental testing.
• Wason's 2-4-6 task demonstrates that participants often fail to generate sets of numbers that would falsify their initial hypothesis.
• Only 21% of students correctly identified the rule (ascending order numbers) on their first try.
• Participants tend to preserve information from example sets in their initial hypotheses.
• Falsification tests are more effective when testing other people's hypotheses.

Hypothesis Testing in Real and Simulated Environments

• Scientists usually take a confirmatory approach.
• Research analysis shows 77% of studies sought to confirm a hypothesis, and 91% supported existing theories.
• The optimal approach for absolute hypotheses is falsification.
• For non-absolute hypotheses, falsification is less critical.

Deductive Reasoning

• Inductive reasoning generalizes from specific examples.
• Deductive reasoning draws certain conclusions from assumed truths.
• Conditional reasoning uses "if-then" statements.
• Affirmation of the consequent and denial of the antecedent are logical errors.
• Modus ponens (if P, then Q and P, thus Q) and modus tollens (if P, then Q and not Q, thus not P) are rules of inference.

Conditional Reasoning: Common Errors and Models

• Affirmation of the consequent (believing if the outcome occurred it means one thing).
• Denial of the antecedent (believing if one thing does not occur it means the outcome won't occur)
• Modus Ponens and Modus Tollens
• Klauer's dual-source model: knowledge and form-based.
• Verschuere's dual-process model: counterexample strategy and intuitive statistical strategy.

Wason Selection Task

• Difficult task requiring participants to determine if a rule is valid
• Abstract versions are harder than concrete versions.
• Matching bias is the tendency to select cards matching the items in the rule
• Performance is better with concrete than abstract scenarios
• Research shows motivation to disprove a rule improves performance on the Wason selection task

Syllogistic Reasoning

• Syllogisms are logical arguments (premises followed by a conclusion).
• Belief bias is the tendency to accept believable conclusions and reject unbelievable ones, even if the conclusion is logically invalid.
• The match-bias often influences performance and decision-making.

Mental Models Theory

• Mental models are internal representations of situations.

Dual-Process Theories

• Type 1 processing is intuitive, fast, and automatic.
• Type 2 processing is reflective, slower, and controlled.
• Default-intervention theory: type 1 automatic processing is followed by type 2 (a more deliberate) processing.
• Logical-intuition model: type 1 processing includes logical intuitive responses, and it conflicts with type 2 response.

Informal Reasoning: Factors and Biases

• Informal reasoning uses knowledge and experience.
• Solution aversion: reluctance to consider solutions that seem unfavorable or difficult.
• Myside bias: seeking out information confirming pre-existing beliefs.
• Argumentation theory: exchange of justifications and arguments

Reasoning and Probabilities

• Bayesian approach: prior beliefs are updated with new evidence to get probability