Deductive Reasoning & Decision Making - PSY 108

Deductive reasoning

Reasoning from general premises to specific conclusions that must be true if the premises are true

Belief-bias effect

Tendency to judge logical validity based on whether the conclusion aligns with personal beliefs

Wason card selection task

A reasoning task showing confirmation bias; people try to confirm a rule instead of testing for falsification

Confirmation bias

Tendency to seek information that confirms a belief rather than challenges it

Decision making

Assessing information and choosing among two or more alternatives

Difference between decision making and deductive reasoning

Decision making involves uncertainty and heuristics while deduction uses logic to reach certain conclusions

Representativeness heuristic

Judging likelihood based on similarity to a prototype rather than logic or statistics

Representativeness example

Assuming someone who loves books is more likely a librarian than a salesperson

Representativeness error

Leads to ignoring statistical information and relying on stereotypes

Small-sample fallacy

Belief that small samples are representative of the population

Small-sample fallacy example

Thinking a small hospital will have the same gender ratios as a large one

Base-rate fallacy

Ignoring statistical base-rate information in favor of descriptive details

Base-rate example

Calling someone an engineer because they “seem like one” despite the base rate being very low

Conjunction fallacy

Believing two events together are more likely than a single event alone

Conjunction example

Judging “bank teller + feminist” as more probable than “bank teller”

Availability heuristic

Estimating likelihood based on how easily examples come to mind

Availability example

Fearing airplane crashes more than car crashes due to vivid media coverage

Recency bias

Tendency to overestimate the likelihood of recent events

Familiarity bias

Events frequently encountered feel more common

Recognition heuristic

If one option is recognized and another is not

Anchoring and adjustment heuristic

Starting with an initial value (anchor) and making insufficient adjustments

Anchoring example

Estimating multiplication differently based on starting with 1×2×3… vs. 8×7×6…

Ecological rationality

The idea that heuristics can be adaptive and effective in real-world environments

Difference from heuristics approach

Heuristics approach highlights errors; ecological rationality argues heuristics work well in natural contexts

Framing effect

Decisions change depending on whether options are framed as gains or losses

Framing effect example

People choose safe options when framed as gains and risky options when framed as losses

Overconfidence

The tendency to overestimate accuracy of judgments and predictions

Domains of overconfidence

Political forecasting

Factors increasing overconfidence

Ignoring alternatives

Hindsight bias

The tendency to believe one “knew it all along” after an event occurs

Hindsight example

Believing an election result was obvious after it happened

Maximizers

People who seek the best possible option; experience more regret

Satisficers

People who choose options that are “good enough”; experience greater happiness and well-being

Classical decision theory

Assumes people know all options

Satisficing (Simon)

Choosing the first acceptable option rather than the optimal one

Role of sample size

Large samples more accurately reflect population characteristics; small samples often produce misleading patterns

Role of media and vividness

Highly vivid or publicized events feel more common regardless of actual frequency

Role of presentation order

Early numbers or information serve as anchors and strongly influence final judgments

Planning fallacy

Tendency to underestimate how long tasks will take