Scatter plot

A scatter plot is a type of plot that displays values, typically for two variables, using cartesian coordinates. Scatter plots are often used when studying the relationship between two variables. Below is a scatter plot showing the relationship between the cost and weight of some product:


Scatter plots can show various types of correlations between variables.

Positive correlation

A positive correlation is one in which the two variables increase together. In the scatter plot below, the red line, referred to as the line of best fit, has a positive slope, so the two variables have a positive correlation.

Negative correlation

When two variables have a negative correlation, one variable increases as the other decreases. In the scatter plot below, variable 2 decreases as variable 1 increases, so the variables have a negative correlation. This is also shown by the fact that the line of best fit has a negative slope.

Non-linear correlation

A non-linear correlation is one in which a pattern exists between the two variables that cannot be described by a straight line. Although the two variables in the figure below do not exhibit any linear correlation, we can see that they do still have a pattern. In this case, the line of best fit is a parabola, so the data has a non-linear correlation.

No correlation

The two variables below do not exhibit a discernible pattern, so they have no correlation.

Sketching a line of best fit

Given that two variables seem to have a linear correlation based on the scatter plot, the following guidelines can be used to sketch a line of best fit:

The figure below shows an example of a line of best fit where an outlier located at (3.5, 5.5) is ignored since most of the points are relatively close together except for said point.