{
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   "cell_type": "code",
   "execution_count": null,
   "id": "a8babbab-fd24-4375-b7fa-797d007b61c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "pip install --upgrade pip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4f47b87d-9127-4127-8230-9246a13f6699",
   "metadata": {},
   "outputs": [],
   "source": [
    "pip install scipy\n",
    "pip install pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9e9759cd-705a-4a0f-83c7-ae08c84fb333",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1edc82b4-4409-4250-9827-c9a217d788b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Person  Vorher  Nachher\n",
      "0       1      12       14\n",
      "1       2      15       16\n",
      "2       3      13       15\n",
      "3       4      14       15\n",
      "4       5      11       13\n",
      "5       6      16       17\n",
      "6       7      17       18\n",
      "7       8      10       11\n",
      "8       9      13       14\n",
      "9      10      14       16\n"
     ]
    }
   ],
   "source": [
    "# Daten in ein Dictionary umwandeln\n",
    "data = {\n",
    "    \"Person\": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n",
    "    \"Vorher\": [12, 15, 13, 14, 11, 16, 17, 10, 13, 14],\n",
    "    \"Nachher\": [14, 16, 15, 15, 13, 17, 18, 11, 14, 16]\n",
    "}\n",
    "\n",
    "# Erstellen des DataFrames\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# Ausgabe des DataFrames\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6ca1af33-a8dd-4c83-a8cd-41671f010a2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T-Statistik: -8.573214099741122\n",
      "P-Wert: 6.3409243600676025e-06\n"
     ]
    }
   ],
   "source": [
    "t_statistic, p_value = stats.ttest_rel(df['Vorher'], df['Nachher'], alternative='less')\n",
    "\n",
    "# Ausgabe der Ergebnisse\n",
    "print(f\"T-Statistik: {t_statistic}\")\n",
    "print(f\"P-Wert: {p_value}\")"
   ]
  }
 ],
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