Correlates are two or more things that tend to occur (or tend NOT to occur) together. Thus, knowing the about the presence of one correlate tells you something about the likelihood of the other correlate. A positive correlation exists if more of one thing tends to mean more of the other thing as well. A negative correlation exists if more of one thing tends to mean less of the other. One may cause (or prevent) the other or they may both be caused (or prevented) by some other factor. It is important to understand that correlation does not imply causality! Here is an example of correlation without causality: Let’s say you are a social scientist and you find that, based on your dataset, people with poor diets are more likely to live in unsafe neighborhoods than people with good diets. Poor diet and living in an unsafe neighborhood are positively correlated. Do you think having a poor diet causes people to live in unsafe neighborhoods? What about the other way around? Probably not. However, they might both be caused by a third factor – low income.