CHP1 Flashcards
HINDSIGHT BIAS
We feel sure we “knew it all along,” overstating our ability to predict outcomes.
Overconfidence
We think we know more than we do, leading to misguided judgment and errors.
Patterns in Random Events
We see false patterns in chance data, creating illusory connections.
Believing Untruths
False news, repetition, biased sources, and group identity all fuel misinformation.
Emotions Override Facts
Strong feelings or biases make us dismiss contradicting evidence.
Critical Thinking
It questions assumptions, checks evidence, and counters misinformation.
Theories
They organize observations and guide testable predictions for new research.
Hypothesis
They’re specific predictions derived from theories, tested to support or refute ideas.
Meta-analysis
It combines multiple studies’ results, yielding stronger overall conclusions.
Explain the importance of preregistration for transparency.
Researchers publicly outline methods and hypotheses beforehand, reducing bias.
Describe the case study method and its advantages/limitations.
It offers detailed insights from one individual but may not generalize widely.
Explain naturalistic observation and how it differs from other methods.
It records natural behavior without interference, describing rather than explaining.
Describe how surveys gather data and why random sampling matters.
Surveys collect self-reports; random sampling ensures a representative group.
Define what it means when two variables are correlated.
They change together, allowing prediction of one from the other.
Explain the difference between positive and negative correlations.
Positive: both variables move in the same direction; negative: they move oppositely.
Describe how scatterplots represent correlations.
Each point shows two variable values; the slope and scatter indicate direction/strength.
Explain what an illusory correlation is and how it leads to mistaken beliefs.
We perceive a relationship where none exists, often due to memorable coincidences.
Discuss regression toward the mean and how it applies to unusual events.
Extreme outcomes tend to return to average on subsequent trials, misleading causal attributions.
Explain why correlation does not imply causation.
A relationship doesn’t prove one variable causes the other; other factors may be involved.
Describe a potential third variable explaining a correlation.
A hidden factor (e.g., temperature) can influence both variables, creating the illusion of cause.
Describe how experimental research isolates cause and effect.
It manipulates one factor while controlling others, pinpointing causal influence.
Explain independent and dependent variables in an experiment.
Independent: manipulated cause; dependent: measured outcome.
Discuss the significance of random assignment in experiments.
It balances groups, minimizing preexisting differences and isolating the treatment’s effect.
Explain the placebo effect and its role in experiments.
Participants improve due to expectations alone; controls separate real from placebo effects.
