Bivariate data is data for two, usually related, variables. Each value of one variable is paired with a value of the other, for example, the height and shoe size of each student in a high school class. Bivariate data can be plotted on a coordinate plane called a scatter plot.

A scatter plot’s x-axis represents one variable, and its y-axis represents the other. By plotting each data pair on a scatter plot, we can visualize the relationship between variables. Scatter plots help us understand whether or not something like height and shoe size are related. Scatter plots also help us identify outliers and clustering in a set of bivariate data.

Outliers are values that are much larger or smaller than most other values in a data set. On a scatter plot, outliers are easy to spot since they appear well above or below most other plotted points. Clustering becomes apparent when points are bunched close together. This tells us something about how common a particular range of values is.