How to Interpret the Scatterplot Chart
In the Trends view, the Scatterplot chart is an excellent tool to quickly and visually correlate two sets of data. This helps you understand if there is a relationship between the two.
In our case, you can look at relationships between:
- An HRV value (like HRV score, or Morning Readiness) to a lifestyle or behavior, like sleep, exercise, weight, blood glucose, and others
- One HRV value (like HRV score) to another HRV value (like total frequency power)
Patterns to look for:
How spread apart are the data points?
- If clustered closely, then there is more likely a relationship
Is there a pattern as you go from left to right?
- If the points go up a hill, then there is a positive relationship between the two variables. When one variable goes up, the other tends to as well.
- If the points go down a hill, then there is a negative or inverse relationship. When one variable goes one, the other tends to go down.
- Many times there will not be any visual relationship. More data might help in those cases
Always keep in mind:
Scatterplots show possible associations or relationships between two variables. However, just because your chart shows something is going on, it doesn’t mean that a cause-and-effect relationship exists.
For example, if your HRV values tend to go up (improve) with lower body weight, it doesn't necessarily mean that lower body weight is causing the change. Lower body weight might be a signal of other changes you've made (such as improved sleep or exercise) that is improving your HRV.
Over time, we'll be introducing tools to help you understand this as well. Let us know what you think at firstname.lastname@example.org