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  "Title": "Obtain and plot bootstrap sampling distributions of the sample\nmean",
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  "Authors@R": "person(\"Ken\", \"Butler\", , \"nxskok@gmail.com\", role = c(\"aut\", \"cre\"))",
  "Description": "Many common tests assume sufficient normality of the data\ndistribution, with the received wisdom that if the sample size\nis \"large\", the normality doesn't matter so much (because of\nthe Central Limit Theorem). It is difficult to judge the\nnormality is good enough, or whether the sample size is big\nenough. A better way to investigate is to obtain a bootstrap\nsampling distribution of the sample mean (by taking repeated\nbootstrap samples), and to assess that distribution for\nnormality. If it is, the normal-theory test will work; if not,\nnot.",
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  "Encoding": "UTF-8",
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  "Date/Publication": "2026-09-23 18:15:19 UTC",
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