mannwhitneyu.ipynb

mannwhitneyu.ipynb

{
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  "metadata": {
    "colab": {
      "name": "Untitled22.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyMKc2s81jdxn4lff+hDcadv",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/nogawanogawa/59dabc33fc091b2208f0af3e4d6975c4/untitled22.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YiM4e4zNeZmW"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from scipy import stats"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sK3N0plNkiqQ"
      },
      "source": [
        "A = np.random.normal(loc=70, scale=10.0, size=100).astype(int) # 平均を70点と想定\n",
        "B = np.random.normal(loc=60, scale=10.0, size=150).astype(int) # 平均を60点と想定"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b2RDdZ_0iKDu",
        "outputId": "d181db1d-03f2-4772-f39f-92dfcb8c2f61"
      },
      "source": [
        "A"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([73, 88, 52, 75, 53, 72, 99, 72, 86, 78, 64, 64, 63, 64, 60, 83, 75,\n",
              "       76, 77, 64, 66, 50, 82, 56, 72, 88, 70, 73, 74, 80, 63, 67, 62, 96,\n",
              "       76, 72, 67, 76, 64, 78, 74, 77, 78, 75, 62, 75, 88, 77, 64, 63, 69,\n",
              "       80, 84, 67, 81, 64, 81, 64, 57, 54, 83, 87, 65, 66, 75, 86, 75, 51,\n",
              "       63, 81, 64, 51, 66, 68, 80, 70, 69, 56, 69, 71, 44, 68, 66, 52, 74,\n",
              "       53, 75, 74, 68, 80, 54, 72, 76, 76, 53, 57, 75, 67, 80, 68])"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mqiKScsBiKP3",
        "outputId": "02e9e41a-6c60-4b44-da0c-3d80c80cd0d3"
      },
      "source": [
        "B"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([79, 61, 76, 50, 58, 61, 59, 60, 83, 59, 55, 69, 77, 47, 48, 48, 81,\n",
              "       64, 77, 54, 53, 57, 66, 74, 72, 40, 69, 56, 58, 62, 60, 49, 55, 62,\n",
              "       65, 65, 54, 81, 72, 63, 62, 76, 59, 64, 56, 64, 69, 78, 47, 58, 62,\n",
              "       62, 73, 64, 79, 49, 73, 51, 43, 59, 62, 56, 63, 68, 69, 62, 65, 61,\n",
              "       54, 48, 72, 69, 69, 61, 49, 64, 64, 61, 49, 68, 63, 50, 46, 75, 68,\n",
              "       49, 60, 73, 68, 44, 49, 66, 79, 48, 71, 79, 64, 59, 58, 40, 60, 78,\n",
              "       37, 62, 60, 53, 47, 61, 53, 54, 46, 43, 56, 56, 60, 65, 61, 49, 52,\n",
              "       57, 61, 60, 62, 55, 60, 53, 42, 78, 48, 63, 61, 64, 50, 62, 58, 55,\n",
              "       51, 76, 70, 59, 58, 41, 65, 55, 39, 47, 63, 67, 68, 59])"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FoORrvHOjtoM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b84d716c-1de4-404f-e528-054ec7876501"
      },
      "source": [
        "stats.mannwhitneyu(A, B, alternative='two-sided')"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MannwhitneyuResult(statistic=11330.5, pvalue=7.859054856897762e-12)"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zb9FefbAhYFT"
      },
      "source": [
        ""
      ],
      "execution_count": 5,
      "outputs": []
    }
  ]
}