Correlation Research

Basic design of correlational research

- Not complicated - Scores for 2 or more variables - Results are expressed as a correlation coefficient that indicated the relation between variables - Can be in the form of relationship studies or prediction studies

How do you analyze and interpret the correlation coefficient?

-Determine the correlation coefficient -A decimal ranging from +1 to -1 -Closer to +1 = positive correlation -Closer to -1 = negative correlation -Closer to 0 = no correlation

Key characteristics of correlational research

-Need a sample size of at least 30 -Variables can be scored -Allows researcher to determine whether and to what degree variables are related -Does not establish casual relationship

Steps in the correlational research process

1) Problem selection 2) Participant and Sample selection 3) Procedure 4) Data analysis and Interpretation

Spearman Rho

Appropriate if the data for at least one variable are expressed as rank or ordinal. - Both variables must be a rank

Pearson R

Appropriate when both variables to be correlated are expressed as continuous data (ratio, interval) - Achievement, personality measures

Correlation does not equal causation

Correlation does not prove that one variable causes the other - only that they have a positive/negative relationship

Correlational research

Involves collecting data to determine to what degree a relationship exists between two quantifiable variables.

Statistical significance

Probability that you could have gotten the results by chance.

Common variance

The extent to which variables vary in a SYSTEMATIC way. (as one goes up, the other goes up, Rise/Run)