02 Terms to Remember
Archival research: Research using secondary datasets collected by others, often cost-effective for examining long-term trends.
Case studies: Detailed examination of particular individuals, groups, companies, or societies to provide rich insights about specific situations.
Causal inference: The primary goal of experimental research, requiring demonstration that changes in independent variables cause changes in dependent variables rather than just correlation.
Coefficient of determination (r²): The percentage of variance in the criterion accounted for by the predictor variable.
Concurrent validity: The extent to which a test predicts a criterion measured at the same time as the test.
Confidentiality: Protection of participant data from unauthorized access or disclosure, particularly important in workplace research involving sensitive information.
Confounding variables: Extraneous variables that vary systematically with independent variables, creating alternative explanations for experimental effects and eliminating the ability to make causal statements.
Construct validity: The extent to which tests or measures actually assess the underlying theoretical constructs they were intended to measure rather than something else.
Content validity: The degree to which a test covers a representative sample of the quality being assessed, established through expert judgment.
Control: The essential feature of experimental design involving systematic management of all variables that might affect results except the one being studied.
Convergent validity: Evidence that a measure relates appropriately to other measures of similar constructs.
Correlation coefficient: Index of relationship strength between two variables, ranging from -1.00 to +1.00 and indicating both direction and magnitude.
Correlational research: Research approach measuring relationships between variables to enable prediction without establishing causation.
Criterion-related validity: The degree to which tests predict important real-world outcomes like job performance, attitudes, or behaviors, demonstrated through predictive or concurrent validity studies.
Cronbach’s alpha: The most common measure of internal consistency reliability that examines relationships among all test items, with values above .70 generally considered acceptable.
Deception: Research technique involving withholding or misrepresenting information to participants, requiring careful justification and thorough debriefing.
Deduction: Approach to science that starts with theory and collects data to test theoretical predictions.
Dependent variables (DVs): Variables measured to assess the effects of experimental manipulations, serving as the criteria, outcomes, consequences, or effects in research studies.
Descriptive statistics: Statistical procedures that summarize and describe data characteristics without making inferences about populations.
Determinism: Scientific assumption that behavior is orderly and systematic rather than random, following discoverable patterns and principles that can be identified and used for prediction.
Discoverability: The optimistic assumption that it’s possible to discover orderliness in behavior through human ingenuity and good methodology.
Divergent validity: Evidence that a measure does not relate strongly to measures of different constructs.
Empiricism: Philosophical assumption that the best way to understand behavior is through systematic observation and testing theories with actual data rather than relying on intuition.
Experience sampling methodology (ESM): Research technique using smartphone apps to capture momentary attitudes and states throughout the day.
External validity: The extent to which research results generalize across other people, settings, and times beyond the specific study context, typically higher in field studies.
Extraneous variables: Variables that might affect study outcomes but are not manipulated by the researcher, also known as “noise.”
Field experiments: Research maintaining experimental control through random assignment while conducted in real-world settings to enhance external validity.
Hawthorne Effect: Phenomenon where people behave differently when they know they’re being studied, potentially making their behavior unrepresentative of natural work situations.
Independent variables (IVs): Variables systematically manipulated by researchers in experiments, serving as the predictors, precursors, antecedents, or causes being studied.
Induction: Approach to science that works from data to theory, starting with observations and building toward theoretical explanations.
Science: Systematic process for generating reliable knowledge that combines empirical observation with logical reasoning to describe, explain, predict, and control phenomena.
Theory: Set of interrelated concepts and propositions that present systematic views of phenomena, serving as “best guesses about universal truths” to guide research and practice.