Exam 2: Nonexperimental Research Flashcards
Nonexperimental research
Research that lacks manipulation of an independent variable and measures variables as they naturally occur. It cannot establish causal relationships.
Correlational research
A type of non-experimental research where the statistical relationship between two variables is measured without manipulation. It cannot establish causality.
Observational research
Research in which behavior is systematically observed and recorded without manipulation of variables. It is non-experimental and cannot infer causality.
Cross-sectional studies
Studies that compare different groups of people at a single point in time. They cannot establish causal relationships.
Longitudinal studies
Studies that follow the same group of individuals over time to observe changes. While they can show changes over time, they do not establish causality.
Cohort effect
Differences between groups in cross-sectional studies that result from the unique experiences of each group (cohort) rather than from age or time effects.
Cross-sequential studies
Studies that combine cross-sectional and longitudinal designs to measure different age groups over time, helping to control for cohort effects.
Internal validity
The extent to which a study can establish a causal relationship between variables, primarily relevant to experimental research.
Scatterplot
A graphical representation of the relationship between two variables, showing individual data points on a two-dimensional grid.
Positive relationship
A statistical relationship where as one variable increases, the other variable also increases (or both decrease together).
Negative relationship
A statistical relationship where as one variable increases, the other variable decreases (and vice versa).
Pearson’s Correlation Coefficient (r)
A statistical measure that indicates the strength and direction of a linear relationship between two variables, ranging from -1 to +1.
Directionality problem
A problem in correlational research where it is unclear whether variable X causes variable Y or vice versa, preventing causal conclusions.
Third-variable problem
A situation in which an unmeasured third variable influences both variables under study, leading to a spurious correlation.
Spurious correlations
Correlations between two variables that appear related but are actually influenced by a third variable or random chance.
Complex correlation
An analysis that explores relationships among multiple variables simultaneously, often through techniques like factor analysis and regression.
Factor analysis
A statistical technique used to identify clusters of related variables (factors) within a larger set of measured variables.
Statistical control
A method used to account for the influence of extraneous variables by including them in the statistical analysis, helping clarify relationships.
Partial correlation
A statistical technique that measures the relationship between two variables while controlling for the effect of one or more other variables.
Regression
A statistical technique that predicts the value of one variable based on the value of another, often used in correlational research.
Predictor variable
The variable that is used to predict the value of another variable (in regression analysis).
Outcome variable (criterion variable)
The variable being predicted in a regression analysis.
Simple regression
A type of regression analysis where one predictor variable is used to predict one outcome variable.
Multiple regression
A regression analysis that uses two or more predictor variables to predict the value of an outcome variable.