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  "body": "\n## Summary\n\nThe breakdown point of an estimator is the smallest fraction of the data that can ruin the estimate.\nRuin means that replacing this fraction by arbitrary values can carry the estimate arbitrarily far.\nIt measures the global robustness of an estimator against gross outliers.\nThe sample mean has breakdown point $1/n$, which tends to $0$.\nThe median has breakdown point close to $1/2$, the largest possible value for equivariant estimators of location.\n\n## Explanations\n\n### L1 human\n\nAsk how many data points an adversary must corrupt to push your estimate as far away as they like.\nFor the average, one corrupted point is enough: making it huge makes the average huge.\nFor the median, the adversary needs to corrupt about half of the points.\nThe breakdown point is this number of points divided by the sample size.\n",
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