Assignment-03-Q5 (Hypothesis Testing).ipynb

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   "source": [
    "# Assignment-03-Q5 (Hypothesis Testing)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Q5. Fantaloons Sales managers commented that % of males versus females walking in to the store differ based on day of the week. Analyze the data and determine whether there is evidence at 5 % significance level to support this hypothesis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "from scipy.stats import norm\n",
    "from scipy.stats import chi2_contingency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Weekdays</th>\n",
       "      <th>Weekend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Female</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Male</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>Female</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>Female</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397</th>\n",
       "      <td>Female</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>398</th>\n",
       "      <td>Female</td>\n",
       "      <td>Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>Female</td>\n",
       "      <td>Female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>400 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Weekdays Weekend\n",
       "0       Male  Female\n",
       "1     Female    Male\n",
       "2     Female    Male\n",
       "3       Male  Female\n",
       "4     Female  Female\n",
       "..       ...     ...\n",
       "395   Female    Male\n",
       "396   Female  Female\n",
       "397   Female  Female\n",
       "398   Female    Male\n",
       "399   Female  Female\n",
       "\n",
       "[400 rows x 2 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the dataset\n",
    "data=pd.read_csv('Database/Faltoons.csv')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Female    287\n",
       "Male      113\n",
       "Name: Weekdays, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.Weekdays.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Female    233\n",
       "Male      167\n",
       "Name: Weekend, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.Weekend.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[287, 233],\n",
       "       [113, 167]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a contingency table\n",
    "obs=np.array([[287,233],[113,167]])\n",
    "obs"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Assume Null Hypothesis as Ho: \n",
    "Independence of categorical variables (% of males versus females walking in to the store does not differ based on day of the week)\n",
    "\n",
    "Thus, Alternative hypothesis as Ha\n",
    "Dependence of categorical variables (% of males versus females walking in to the store does differ based on day of the week)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15.434065934065934,\n",
       " 8.54342267020237e-05,\n",
       " 1,\n",
       " array([[260., 260.],\n",
       "        [140., 140.]]))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Chi2 contengency independence test\n",
    "chi2_contingency(obs) # o/p is (Chi2 stats value, p_value, df, expected obsvations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compare p_value with α = 0.05"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Inference:\n",
    "As (p_value = 0) < (α = 0.05); Reject Null Hypothesis\n",
    "i.e. Dependence of categorical variables \n",
    "Thus, % of males versus females walking in to the store does differ based on day of the week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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