Scatter plots are a useful data visualization that is useful to compare two different quantitative variables. Scatter plots are basic depictions of data, but also convey a great amount of information. These plots also have a number of extensions that produce even further analysis of your data.
A scatter plot is depicted on a cartesian plane. One variable has values which lie on the x-axis, and the other on the y-axis. In some cases, variables on the x-axis are referred to as explanatory variables, and variables on the y-axis as response variables. Here is an example of a scatter plot chart.
Scatter Plot Uses
Scatter Plot Charts compare two quantitative variables. When using a scatter plot we want to see how two variables relate. Known as correlation, variables can have high, low, or no correlation. For example, flower petal length and petal width have high correlation. The longer a flower petal is, the wider it will be in general.
Another thing that scatter plots are able to show you is clumping or groupings. Again looking at the example, you can see that the different colors are more clumped together. Gleaning information from this, we can tell that, in general, the Iris-setosa is the smallest species followed by the Iris-versicolor and then the largest being the Iris-virginica. Within each of these species, longer petal length still correlates to larger petal width as well.
You can use scatter plots in many different ways, but can be quite useful when attempting to gain information about how two quantitative variables relate to each other. Finding a correlation between them is always useful, as is finding groupings.