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                      "value": "If the mean of the transformed data is not equal to the original variance, indicating a lack of convergence in the O'Brien transform."
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                      "value": "Defines how to handle input NaNs."
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                              "value": ": if a NaN is present in a sample, all elements of the   transformed sample will be NaN."
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                              "value": ": NaNs will be omitted when computing reducing statistics for the   transform, but NaNs in the sample will remain NaNs in the transformed sample."
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              "value": "Used to test for homogeneity of variance prior to running one-way stats. Each array in "
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              "value": "*samples"
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              "value": " is one level of a factor. Significant results of "
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              "value": " on the transformed data suggest that the variances of the underlying distributions are unequal. See Maxwell and Delaney "
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              "label": "1"
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              "value": ", p.112."
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        "value": "We'll test the following data sets for differences in their variance.\n\n"
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        "value": "x = [10, 11, 13, 9, 7, 12, 12, 9, 10]\ny = [13, 21, 5, 10, 8, 14, 10, 12, 7, 15]\n",
        "execution_status": "success",
        "out": ""
      },
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        "value": "\nApply the O'Brien transform to the data.\n\n"
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        "value": "from scipy.stats import obrientransform\ntx, ty = obrientransform(x, y)\n",
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      },
      {
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        "value": "\nUse `scipy.stats.f_oneway` to apply a one-way ANOVA test to the\ntransformed data.\n\n"
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        "value": "from scipy.stats import f_oneway\nF, p = f_oneway(tx, ty)\n",
        "execution_status": "success",
        "out": ""
      },
      {
        "__type": "Code",
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        "value": "p\n",
        "execution_status": "failure",
        "out": "np.float64(0.13141394770403342)\n"
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      {
        "__type": "Text",
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        "value": "\nIf we require that ``p < 0.05`` for significance, we cannot conclude\nthat the variances are different."
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  "references": [
    ".. [1] S. E. Maxwell and H. D. Delaney, \"Designing Experiments and",
    "       Analyzing Data: A Model Comparison Perspective\", Wadsworth, 1990."
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