What is Survivor Bias?
In: 1017
Survivor Bias is when you only consider data that meets a condition (such as surviving) and not correcting for that condition. By forcing data to meet a condition you are limiting your data. When doing research you have to limit your conclusion when you limit your data.
e.g.
Theory: homes built 200 years ago were more beautiful. Reality: Only the prettiest homes built 200 years ago survived because the rest were knocked down. Error: limited data to only surviving homes built 200 years ago and ignored the non-surviving ones. Corrected: The 200 year old homes I see today are beautiful”
Theory: We never had car seats when we were young and we grew up fine so car seats are unnecessary. Reality: not everyone did grow up fine. Error: not including major injuries or deaths due to lack of car seats. Corrected: “Thankfully I never got in a bad accident so I never had to test a car seat’s safety”.
Theory: They don’t make quality cars like they used to *pats 50 year old car*. Reality: Not many are left on the road. Error: Just because one (or some) survived doesn’t mean all cars built at that time could or would have survived or that they were built better. Corrected: “This car was built and maintained well or else it wouldn’t be here today”
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