We want to interpret the given scatter plot. To do so, we can start by reviewing different patterns of associations between two data sets that can be shown using scatter plots.
Notice that we can use the shape of the distribution of a scatter plot to determine the type of the association. Let's look at the given scatter plot!
We can see that the points lie in a shape of a curve , so the association is nonlinear. Notice that as the length of the sign increases, the paint used also increases. This means that the scatter plot shows a positive nonlinear association. Next, let's recall some important definitions.
Outlier
Cluster
An outlier is a data point that is set off from the other data points.
A cluster is a group of points that lie close together.
With these definitions in mind, we can finally make some conclusions about the outliers and clusters in our graph.
There appears to be an outlier at (8,2).
There is a cluster of data from 1 feet to 3 feet.
Note that clusters and outliers are found by observing a graph. Therefore, they are subjective and a different observer can interpret the graph differently. Our solution is just an example solution.
