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  "body": "\n## Summary\n\nAn ancillary statistic is a [[statistic|0Q5CG2NEQ8]] whose distribution does not depend on the parameter.\nOn its own it carries no information about the parameter, yet it can tell how precise the data are.\nFisher proposed to condition inference on ancillary statistics, and [[Basu's theorem|6GATRFMJYY]] shows that they are independent of complete sufficient statistics.\n\n## Explanations\n\n### L1 human\n\nSome features of the data do not depend on the quantity you want to learn.\nFor measurements with an unknown true value and known noise, the difference between two measurements does not depend on the true value.\nSuch a feature is ancillary: its distribution is known in advance.\nIt cannot tell you where the true value is, but it can tell you how spread out your data happened to be.\n",
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