Correlational

Correlational is an adjective used in statistics to describe a relationship between two or more variables in which changes in one variable tend to be associated with changes in another, without experimental manipulation. Researchers use correlational methods to quantify the strength and direction of associations using observed data.

A correlation coefficient expresses the degree of linear association. Pearson's r ranges from -1 to +1, with 0 indicating no linear relationship. Spearman's rho and Kendall's tau assess monotonic relationships and are appropriate for ordinal data or non-normal distributions. Scatterplots help visualize the relationship; correlation does not reveal causation.

Correlational research designs include cross-sectional studies that measure variables at a single time point and longitudinal studies that track changes over time. Key limitations: cannot establish causality; vulnerable to confounding variables and bidirectional or reverse causation; outliers and restricted range can distort the observed association.

In practice, correlational analyses are used across disciplines (psychology, economics, epidemiology) for hypothesis generation, risk assessment, and identifying associations to study further with experimental designs. Interpreting correlation requires considering measurement reliability, sample representativeness, and the broader theoretical context.