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              "value": "When calculating the power of an experiment (power = probability of rejecting the null hypothesis when a specific alternative is true) the non-central F statistic becomes important.  When the null hypothesis is true, the F statistic follows a central F distribution. When the null hypothesis is not true, then it follows a non-central F statistic."
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                      "value": "Drawn samples from the parameterized noncentral Fisher distribution."
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        "value": "In a study, testing for a specific alternative to the null hypothesis\nrequires use of the Noncentral F distribution. We need to calculate the\narea in the tail of the distribution that exceeds the value of the F\ndistribution for the null hypothesis.  We'll plot the two probability\ndistributions for comparison.\n\n"
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    "       From MathWorld--A Wolfram Web Resource.",
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    ".. [2] Wikipedia, \"Noncentral F-distribution\",",
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