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.
Positive correlation
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.
Negative correlation
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).