Psyc 333 Study Guide Flashcards

Vocabulary flashcards based on lecture notes covering causality, experiments, surveys, culture of honor, and statistical thinking.

Causality

Identifying what causes what; a tricky goal in psychology and science.

Randomized Experiments

A powerful way to infer cause-and-effect relationships between variables, involving random assignment of participants to different groups.

Random Assignment

Means each participant has an equal chance to end up in any group, helping ensure the groups are similar in all ways except the treatment.

Equal Distribution of Characteristics

Helps in minimizing researcher bias and balances out other confounding variables among groups.

Internal Validity

How confident we can be that the independent variable truly caused the effect on the dependent variable.

Random Sampling

How you pick people from a population to be in your study; helps with generalizability to the broader population.

External Validity

Generalizing results to a population.

t-test

Checks if two means (averages) are significantly different from each other.

F-test

Often used in analysis of variance (ANOVA); used to compare two groups.

Chi-square (χ²) test

Often refers to a 2x2 table comparison, used for categorical data.

p-value

The probability of getting your observed data (or something more extreme) if there really was no true effect.

Demand Characteristics

When participants pick up clues about the purpose of the study or what behavior is expected, and then alter their behavior.

Expectancy Effects (Observer Expectancy)

When a researcher’s expectations unintentionally influence participants.

Systematic Error

Errors that bias the results in a particular direction.

Randomized Controlled Trials (RCTs)

Considered the “gold standard” for testing things because of their strong causal inference.

Propensity Score Matching

Technique: in a large observational study, analysts can mathematically create groups that are similar on a host of variables to mimic what randomization would have achieved.

Converging Evidence

Using multiple methods that converge on the same finding, because each method’s strengths can make up for the weaknesses of others.

Parsimonious

The simplest explanation that fits all the evidence.

Construct Validity

Did you actually measure what you intended to measure?

External Validity

Do the results generalize to other people, places, times?

Statistical Conclusion Validity

Did you use the right statistical methods, and do you have enough data to support your conclusions?

Internal Validity

Did you properly establish cause-and-effect without confounds?

The Unsolvable Problem of Surveys

If people don’t want to tell you something, they won’t – and there’s no way to get the truth if they choose to hide or misrepresent it.

Non-attitudes

For many things, people don’t have stable, coherent attitudes at all!

The Miracle of Aggregation

When you have a large enough sample, the average outcome will be close to the true average of the whole population, and random individual quirks or errors tend to cancel out.

Attitude vs. Behavior

Attitudes and behaviors are often only weakly correlated.

Specificity Matching

Attitudes predict behavior better when the attitude is measured at a level specific to the behavior.

Channel Factor

A small prompt or situational factor that helps “channel” an intention into actual behavior.

Culture of Honor

A social framework where people (particularly men) are highly sensitive to reputational slights and insults, and are expected to defend their honor.

Law of Large Numbers

A statistical principle: when you have a large enough sample, the average outcome will be close to the true average of the whole population, and random individual quirks or errors tend to cancel out.

p-value (Statistical Significance)

The probability of obtaining an effect at least as extreme as the one in your sample data, assuming there is truly no effect in the population.

Effect Size (Cohen’s d)

A standardized measure of difference between two groups.

Standard Deviation (SD)

A measure of variability in a set of numbers; roughly the average distance of scores from the mean of those scores.

Random Sampling

Selecting participants from a population such that each person has an equal chance of being chosen.

Random Assignment

Dividing your sample into groups by chance.

Propensity Score Matching

A statistical technique used in observational studies to create groups that are as similar as possible on other variables except the one of interest.

Parsimony (Occam’s Razor)

The principle that we should prefer simpler explanations that account for all the data over more complicated ones.

Demand Characteristics

Cues in an experiment that tip off participants to what the study is about or what behavior is expected from them.

Expectancy Effect (Experimenter Expectancy)

When a researcher unintentionally influences participants to behave in a way that confirms the researcher’s hypothesis.