Correlation Coefficient

Correlation coefficient refers to the type of relationship between variables that allows one to make predications from one variable to another. Correlations does not mean that one variable causes another to occur, but predictions can be made based on the data of one variable.

The formula for correlation coefficients varies and depends on the type data being analyzed. The types of data include nominal, ordinal, interval, and ratio scales of measurement. The Pearson Product-Moment Correlation Coefficient is the most commonly used correlation coefficient.

The Pearson Product-Moment is usually referred to as Pearson’s r (the r being the statistical notation) and is used to measure data types of interval or ratio (Jackson, 2009).

r = ∑ zx zy N Where z is the z score of the variable, x and y are the variables (the data of such variables), and N being the number of variables or the number of participants.

The other types of formula used in calculation correlation coefficient are the Spearman’s rank order, point-biserial, and phi. The use of these formulas requires that the data is in nominal or ordinal scales of measurement.

Correlations are either positive or negative and a positive correlation is usually no greater than 1 Correlation is typically illustrated using a scatter plot graph