We look at how much changes in one data flow can predict changes in another.

We calculate how often the behavior of two charts is in sync throughout the given time period — like if they both increase or decrease at the same time, or if one increases when the other decreases. The more predictable the behavior, the higher the correlation.

We always look for correlations between data from different lifestyle categories. Each chart has a specific list of data flows we look for correlations with to ensure you get meaningful insights.

So you won’t see a chart that shows a correlation between your step count and distance walked — they belong to the same category, and it’s obvious the correlation will always be 100%.