Discover statistically significant correlations in the quantified self data
This correlation engine analyzes the daily metrics to find meaningful patterns.
Statistical Analysis: Uses Pearson correlation coefficient (r) to measure the strength and direction of relationships between metrics.
Confidence Levels:
Correlation does not imply causation. These insights show associationsbetween metrics, not cause-and-effect relationships.
Total caffeine consumed • Average daily humidity
When Caffeine Intake goes up, Humidity tends to decreases. High statistical confidence (p < 0.01).
Time spent writing • Clear weather (cloudiness < 30%)
On days when Clear weather (cloudiness < 30%), Writing Time tends to be higher. High statistical confidence (p < 0.01).
Number of coffee servings • Coffee cups yesterday
When Coffee goes up, next day's Coffee Cups tends to increases. Moderate statistical confidence (p < 0.05).
Time spent writing • Number of coffee servings
When Writing Time goes up, Coffee Cups tends to decreases. Moderate statistical confidence (p < 0.05).
Total caffeine consumed • Sleep score yesterday
When Sleep goes up, next day's Caffeine Intake tends to decreases. Moderate statistical confidence (p < 0.05).
Total caffeine consumed • Coffee cups yesterday
When Coffee goes up, next day's Caffeine Intake tends to increases. Moderate statistical confidence (p < 0.05).