Correlation Is Not Causation
Just because two metrics move together doesn't mean one causes the other. This is vital when analyzing user data, as a feature launch might correlate with higher signups when the real cause was a marketing campaign.
Correlation isn't causation; just because two variables move together doesn't mean one causes the other. They could both be driven by a third, hidden factor. This is a core principle in data analysis and interpreting A/B tests. For example, a feature launch might correlate with a rise in user engagement, but the actual cause could be a concurrent marketing campaign. The footgun is acting on a correlation as if it's causation, leading you to invest in the wrong features or misinterpret business performance.
Read the original → Wikipedia: Correlation and causation
- #analytics
- #metrics
- #statistics
- #logical fallacy
Get five bites like this every day.
Tezvyn delivers a daily feed of 60-second tech bites with quizzes to lock in what you learn.