Scatter charts and correlation

What are Scatter Plots?

A Scatter plot is used to visualize relationships between two or more variables.

A relationship between two values is known as correlation. You can have a positive correlation. You can have a negative correlation. And you can have no correlation.

Testing for correlation is useful when you want to establish if there are possible connections between two variables.

A scatter plot can also be useful for identifying other patterns in data. We can divide data points into groups based on how closely sets of points cluster together.

Scatter plots can also show if there are any unexpected gaps in the data and if there are any outlier points.

How to read a Scatter Chart

Correlation can be charted as shown below. Where one variable is charted against a second in a scatter plot. A strong positive correlation will show a line or curve increasing as you move right across the chart. This can be seen in 1 below.

A strong negative correlation will show a line or curve decreasing as you move right across the chart. This can be seen in 4 below (bottom-right).

For a better view of the above image, see the PDF attached.

When a scatter plot is used to look at a predictive or correlational relationship between variables, it is common to add a trend line. This trend line is the mathematical best fit for the data. This can provide an additional sign as to how strong the relationship between the two variables is. And it also shows if there are any unusual points affecting the computation of the trend line.