ztest.ipynb

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     "text": [
      "    Name  Score\n",
      "0    Tom     66\n",
      "1   nick     71\n",
      "2  krish     49\n",
      "3   jack     58\n",
      "4    sam     61\n"
     ]
    }
   ],
   "source": [
    "#creating a dataset from scratch into pandas\n",
    "data = {'Name':['Tom', 'nick', 'krish', 'jack', 'sam'],\n",
    "        'Score':[66, 71, 49, 58, 61]}\n",
    "# Creating DataFrame\n",
    "grade_df = pd.DataFrame(data)\n",
    " \n",
    "print(grade_df)"
   ]
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   "cell_type": "code",
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     "data": {
      "text/plain": [
       "(-1.4907119849998598, 0.06801856405707181)"
      ]
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     "execution_count": 54,
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   "source": [
    "#lets define a method for z-test which takes population mean, variance and the sample to calculate and return z-score and p-value\n",
    "import math\n",
    "def z_test(pop_mean, pop_std, sample):\n",
    "    z_score = (sample.mean() - pop_mean)/(pop_std/math.sqrt(len(sample)))\n",
    "    return z_score, stats.norm.cdf(z_score)\n",
    "\n",
    "z_test(67, 9.0, grade_df.Score)"
   ]
  },
   {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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