23.Advertising Data Set For Linear Regression.ipynb

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      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>TV</th><th scope=col>radio</th><th scope=col>newspaper</th><th scope=col>sales</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>230.1</td><td>37.8 </td><td>69.2 </td><td>22.1 </td></tr>\n",
       "\t<tr><td> 44.5</td><td>39.3 </td><td>45.1 </td><td>10.4 </td></tr>\n",
       "\t<tr><td> 17.2</td><td>45.9 </td><td>69.3 </td><td> 9.3 </td></tr>\n",
       "\t<tr><td>151.5</td><td>41.3 </td><td>58.5 </td><td>18.5 </td></tr>\n",
       "\t<tr><td>180.8</td><td>10.8 </td><td>58.4 </td><td>12.9 </td></tr>\n",
       "\t<tr><td>  8.7</td><td>48.9 </td><td>75.0 </td><td> 7.2 </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       " TV & radio & newspaper & sales\\\\\n",
       "\\hline\n",
       "\t 230.1 & 37.8  & 69.2  & 22.1 \\\\\n",
       "\t  44.5 & 39.3  & 45.1  & 10.4 \\\\\n",
       "\t  17.2 & 45.9  & 69.3  &  9.3 \\\\\n",
       "\t 151.5 & 41.3  & 58.5  & 18.5 \\\\\n",
       "\t 180.8 & 10.8  & 58.4  & 12.9 \\\\\n",
       "\t   8.7 & 48.9  & 75.0  &  7.2 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| TV | radio | newspaper | sales |\n",
       "|---|---|---|---|\n",
       "| 230.1 | 37.8  | 69.2  | 22.1  |\n",
       "|  44.5 | 39.3  | 45.1  | 10.4  |\n",
       "|  17.2 | 45.9  | 69.3  |  9.3  |\n",
       "| 151.5 | 41.3  | 58.5  | 18.5  |\n",
       "| 180.8 | 10.8  | 58.4  | 12.9  |\n",
       "|   8.7 | 48.9  | 75.0  |  7.2  |\n",
       "\n"
      ],
      "text/plain": [
       "  TV    radio newspaper sales\n",
       "1 230.1 37.8  69.2      22.1 \n",
       "2  44.5 39.3  45.1      10.4 \n",
       "3  17.2 45.9  69.3       9.3 \n",
       "4 151.5 41.3  58.5      18.5 \n",
       "5 180.8 10.8  58.4      12.9 \n",
       "6   8.7 48.9  75.0       7.2 "
      ]
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   "source": [
    "Data <- read.csv('DataSets/Advertising.csv')\n",
    "head(Data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "input<- Data$TV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "output<- Data$sales"
   ]
  },
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   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = output ~ input, data = Data)\n",
       "\n",
       "Coefficients:\n",
       "(Intercept)        input  \n",
       "    7.03259      0.04754  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LM<-lm(output~input, data=Data)\n",
    "LM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = output ~ input, data = Data)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-8.3860 -1.9545 -0.1913  2.0671  7.2124 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept) 7.032594   0.457843   15.36   <2e-16 ***\n",
       "input       0.047537   0.002691   17.67   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 3.259 on 198 degrees of freedom\n",
       "Multiple R-squared:  0.6119,\tAdjusted R-squared:  0.6099 \n",
       "F-statistic: 312.1 on 1 and 198 DF,  p-value: < 2.2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summary(LM)"
   ]
  }
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