Simpson's Paradox

Simpson's Paradox is a situation in statistics where a trend appears in different groups of data but reverses or disappears when the groups are combined.

Example:

Imagine two tutoring centers, Center A and Center B, are helping students pass an exam. Overall, Center B has a higher pass rate than Center A. At first glance, Center B seems to be more successful.

Now, let's divide the students into two groups: those taking the exam for the first time and those who are retaking it. Among first-timers, Center A has a higher pass rate. Among repeat takers, Center A also has a higher pass rate!

As first, these results seem contradictory, but they can be explained if Center A has a higher percentage of first-time test takers. If first-time test takers are less likely to pass, this could explain why Center A has a lower pass rate overall.

Simpson's Paradox teaches us that we can misinterpret data if we're not careful. It's important to analyze subgroups within data for possible confounding variables. To see a real-life example of Simpson's paradox, read my blog post about The Kidney Conundrum.

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