ABSTRACT
Correlation is the measurement of the extent to which pairs of related values of two variables tend to change together or ‘co-vary’; it is a standardised measure of co-variation. If one variable tends to increase with the other, the correlation is positive. If the relationship is inverse, it is a negative correlation. A lack of relationship is signified by a value close to zero but a value of zero could occur for a curvilinear relationship. These relationships can be illustrated in a scatterplot. Two major calculations for correlation are introduced. l Pearson’s (r) product moment correlation – based on variance in two sets of scores;
r is high when large deviations are paired with large deviations and small with small. A parametric test. Effect size and power are considered for correlations.
