In statistics, a recursive relationship between two variables is one in which the causal effects run in only one direction.
Regression is a statistical technique that is used to learn more about the relationship between an independent (predictor) variable and a dependent (criterion) variable.
In statistics, a sampling distribution is a theoretical mathematical distribution of all the possible sample outcomes that can be obtained by selecting samples from a population.
A sampling weight is a statistical correction factor that compensates for a sample design that tends to over- or under-represent various segments within a population.
Secondary analysis is the practice of analyzing data that have already been gathered by someone else, often for a distinctly different purpose.
In statistics, specification is the practice of seeing if a particular relationship among variables remains the same in different segments of a population.
In statistics, spuriousness occurs when two variables that are statistically related to each other, but have no causal relationship.
A standard error is a statistical measure of the amount of variation in a sampling distribution.
Standardization is a statistical technique that gives different units of measurement a common base for purposes of comparison.
In statistics, a suppressor variable is a variable that, when controlled, has the effect of strengthening the relationship between two other variables.
Variance is a statistical measure of the degree to which scores in a distribution differ from one another, especially in relation to the mean of the distribution.
In statistics, a z-score indicates how many standard deviations an observation is above or below the mean.