The Nature of Correlational Research

• The major characteristic of correlational research is seeking out associations among variables.

Purposes of Correlational Research

• Correlational studies are carried out either to help explain important human behaviors or to predict likely outcomes.
• If a relationship of sufficient magnitude exists between two variables, it becomes possible to predict a score on either variable if a score on the other variable is known.
• The variable that is used to make the prediction is called the predictor variable.
• The variable about which the prediction is made is called the criterion variable.
• Both scatterplots and regression lines are used in correlational studies to predict a score on a criterion variable.
• A predicted score is never exact. As a result, researchers calculate an index of prediction error, which is known as the "standard error of estimate."

Complex Correlational Techniques

• Multiple regression is a technique that enables a researcher to determine a correlation between a criterion variable and the best combination of two or more predictor variables.
• The coefficient of multiple correlation (R) indicates the strength of the correlation between the combination of the predictor variables and the criterion variable.
• The value of a prediction equation depends on whether it predicts successfully with a new group of individuals.
• When the criterion variable is categorical rather than quantitative, discriminant function analysis (rather than multiple regression) must be used.
• Factor analysis is a technique that allows a researcher to determine whether many variables can be described by a few factors.
• Path analysis is a technique used to test a theory about the possibility of causal connections among three or more variables.

Basic Steps in Correlational Research

• These include, as in most research, selecting a problem, choosing a sample, selecting or developing instruments, determining procedures, collecting and analyzing data, and interpreting results.

Correlation Coefficients and Their Meaning

• The meaning of a given correlation coefficient depends on how it is applied.
• Correlation coefficients below .35 show only a slight relationship between variables.
• Correlations between .40 and .60 may have theoretical and/or practical value depending on the context.
• Only when a correlation of .65 or higher is obtained can reasonably accurate predictions be made.
• Correlations over .85 indicate a very strong relationship between the variables correlated.

Evaluating Threats to Internal Validity in Correlational Research

• Threats to the internal validity of correlational studies include subject characteristics, location, instrument decay, data collection, and testing.
• Results of correlational studies must always be interpreted with caution, because they may suggest, but they cannot establish, causation.