bivariate correlation

An association that involves exactly two variables. Also called bivariate as

mean:

An arithmetic average; a measure of central tendency computed from the sum of all the scores in a set of data, divided by the total number of scores.sociation

Effect size

The magnitude, or strength, of a relationship between two or more variables.

Statistically significant

In NHST, the conclusion assigned when when p < .05; that is, when it is unlikely the result came from the null hypothesis population.

Replication

The process of conducting a study again to test whether the result is consistent.

outlier

A score that stands out as either much higher or much lower than most of the other scores in a sample.

Restriction of range:

In a bivariate correlation, the absence of a full range of possible scores on one of the variables, so the relationship from the sample underestimates the true correlation.

Curvilinear association:

An association between two variables that is not a straight line; instead, as one variable increases, the level of the other variable increases and then decreases (or vice versa). See also negative association, positive association, zero association.

Directionality problem:

In a correlational study, the occurrence of both variables being measured around the same time, making it unclear which variable in the association came first. See also temporal precedence

Reverse causation

In a study that finds a relationship between variables A and B, the plausible inference that either A could cause B or that B could cause A.

Third variable problem

In a correlational study, the existence of a plausible alternative explanation for the association between two variables. See also internal validity.

Spurious association:

A bivariate association that is attributable only to systematic mean differences on subgroups within the sample; the original association is not present within the subgroups.

Moderator

A variable that, depending on its level, changes the relationship between two other variables.

Multivariate design:

A study designed to test an association involving more than two measured variables.

Longitudinal design:

A study in which the same variables are measured in the same people at different points in time.

Cross sectional correlation:

:In a longitudinal design, a correlation between two variables that are measured at the same time.

Autocorrelation

In a longitudinal design, the correlation of one variable with itself, measured at two different times.

Cross lag sectional

In a longitudinal design, a correlation between an earlier measure of one variable and a later measure of another variable.

Multiple regression

A statistical technique that computes the relationship between a predictor variable and a criterion variable, controlling for other predictor variables. Also called multivariate regression.

Control for

Holding a potential third variable at a constant level (statistically or experimentally) while investigating the association between two other variables. See also control variable, multiple regression.

Criterion variable

The variable in a multiple-regression analysis that the researchers are most interested in understanding or predicting. Also called dependent variable.

Predictor variable

A variable in multiple-regression analysis that is used to explain variance in the criterion variable. Also called independent variable.

Parisomny

The degree to which a theory provides the simplest explanation of some phenomenon. In the context of investigating a claim, the simplest explanation of a pattern of data; the best explanation that requires making the fewest exceptions or qualifications.

Mediator

A variable that helps explain the relationship between two other variables. Also called a mediating variable.