Scatter plots show data as points using Cartesian coordinates (x/y-axis).
Scatter plots can have two measures, one for the X-axis and the other for the Y-axis, and one attribute, which determines the meaning of each point in the plot.
Scatter plots are best used to visualize the relationship and correlation between two measures. It shows how two measures relate to one another.
Scatter plots have the following sections: Measure (X-axis), Measure (Y-axis), Attribute, and Configuration.
The example above (Image 1), we want to see if there is correlation between Huddle Completion and Test Score; iff a user has a higher huddle completion %, does it mean the user is likely to have a higher test score (and vice verse)?
To start, we select the Scatter Plot and customize as follows:
- Measure 1 (X-Axis): Huddle Completion % – we have set it to “Average” as it is a percentage metric (%).
- Measure 2 (Y-Axis): Test Score – we have set it to “Average” as it is a percentage metric (%)
- Attribute: User – as we want both measures broken down by Users.
The resulting scatter plot indicates that users with a higher Huddle Completion % often have higher Test Scores – these two metrics are positively correlated.
- Colors: We can configure the color of the x-y dot for each user’s Huddle Completion % vs. Test Score
- X-Axis & Y-Axis: Configure to show and rotate the labels on the scatter plot. The scale option is to scale the start and end point of the X-Axis & Y-Axis.
We can adjust the scale for each Measure to omit outliers as well:
To learn about other charts, please click here.