You may have heard that 68% of statistics are made up on the spot. Or that all models are wrong, but some are useful. Perhaps you’ve witnessed an event that had less than a 1% chance of happening or (ideally) placed a bet with impossible odds and won.
These, among many others, are some of the reasons analytics and statistics can be so terrifying or hard to understand. For example, sometimes a single set of data can be interpreted multiple ways to tell different sides of the same story. Not surprisingly, that makes some people skeptical about how data is used.
One clear example of this is Simpson’s Paradox, which is a phenomenon where a trend occurs in subsections of data but is not present in the entire set (or vice versa). Take COVID data, something we’ve all heard plenty about over the past year. In February, an analysis done