Correlations

Sometimes, researchers may choose to more passively interact with a phenomenon, rather than to intervene and manipulate the behaviors of interest.

For instance, perhaps a scientist wants to know if there’s an association between eating a plant-based diet and sleep. In this case, she quantitatively measures two variables by asking participants to report how many vegetables they consumed that day, and later, how many hours they slept.

This design is known as correlational research—examining whether relationships exist between two variables.

After collecting both series of measurements, the researcher can visualize the data for each unit, in this case each person, on a graph—a scatterplot—with the variables—daily vegetable consumption and amount of sleep—placed on either axis.

Statistically, correlations are determined by calculating the correlation coefficient, commonly denoted as r—a number between -1 and 1 that indicates the direction, the sign, of the association and its overall strength, how tight the points align.

Here, the correlation could be positive, which means that the two variables move in the same direction. That is, people who consumed very few veggies slept less, where