Human Service

The correlation is a way to measure how associated or related two variables are. The researcher looks at things that already exist and determines if and in what way those things are related to each other. The purpose of doing correlations is to allow us to make a prediction about one variable based on what we know about another variable.

For example, there is a correlation between income and education. We find that people with higher incomes have more years of education. (You can also phrase it that people with more years of education have higher incomes.) When we know there is a correlation between two variables, we can make a prediction. If we know a group's income, we can predict their years of education.

There are two types or directions of correlation. In other words, there are two patterns that correlations can follow. These are called positive correlation and negative correlation.

Remember that in a correlational study, the researcher is measuring conditions that already exist. He or she is asking questions of a sample of participants, and finding out in what way pairs of variables are related. For example, a researcher could ask about the participants' yearly income and years of education, to see if those two attributes are correlated.

In a positive correlation, as the values of one of the variables increase, the values of the second variable also increase. Likewise, as the value of one of the variables decreases, the value of the other variable also decreases. The example above of income and education is a positive correlation. People with higher incomes also tend to have more years of education. People with fewer years of education tend to have lower income.

Here are some examples of positive correlations:

1. SAT scores and college achievement--among college students, those with higher SAT scores also have higher grades

2. Happiness and helpfulness--as people's happiness level increases, so does their helpfulness (conversely, as people's happiness level decreases, so does their helpfulness)

In a negative correlation, as the values of one of the variables increase, the values of the second variable decrease. Likewise, as the value of one of the variables decreases, the value of the other variable increases.

This is still a correlation. It is like an "inverse" correlation. The word "negative" is a label that shows the direction of the correlation.

There is a negative correlation between TV viewing and class grades--students who spend more time watching TV tend to have lower grades (or phrased as students with higher grades tend to spend less time watching TV).

Here are some other examples of negative correlations:

1. Education and years in jail--people who have more years of education tend to have fewer years in jail (or phrased