ABSTRACT
This chapter shows that correlation measures how variables are related, direct and inverse relationships. It discusses that correlation does not infer causality. Correlation refers to the extent to which two variables are related across a group of participants. In a direct relationship, those who score high on one variable tend to score high on the other, and those who score low on one variable tend to score low on the other. In an inverse or negative relationship, those who score high on one variable tend to score low on the other. It is important to note that just because a correlation between two variables is observed, it does not necessarily indicate that there is a causal relationship between the variables. In fact, there might not be any causal relationship at all between the two variables because a host of other variables might account for the relationship between self-concept and depression.
