Scatterplots

Interpreting the Data

Scatterplots illustrate the relationship between two variables, such as achievement and growth. Specifically, scatterplots enable you to visually examine the relationship between the variables and answer the question, "As variable A changes, what happens to variable B?" In the case of achievement and growth, you might ask, "As the average achievement of students in a division increases, does the average growth also increase?" In other words, is there a relationship between achievement and growth?

When data points on a scatterplot are distributed somewhat symmetrically along a horizontal or vertical line, there is little to no relationship between the selected variables.

No Relationship

Additionally, a more diagonal pattern indicates that the variables are related. The closer the pattern is to a diagonal line, the stronger the relationship.

Variables are positively correlated if one variable increases or decreases as the other variable increases or decreases. A good example of positive relationship is that of temperature and the sale of ice cream. As the temperature rises, ice cream sales rise with it.

Positive Relationship

Variables are negatively correlated if they move in opposition to each other. In other words, when one increases, the other decreases. For example, as the temperature goes up, sales of hot chocolate go down.

Negative Relationship

When interpreting the relationship between two variables on a scatterplot, it's important to remember that correlation does not prove causation. If variable B increases as variable A increases, that does not necessarily mean that changes in variable A caused the changes in variable B. Also, if the graph contains only a small number of data points, a correlation might be suggested that does not exist in a larger set of data.