Assignment2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Solutions to Assignment 2\n",
    "\n",
    "## (ISLR #1) [25 marks]\n",
    "\n",
    "The null hypotheses for each row variable (e.g. TV) is that TV advertising has no effect on sales, holding the level of radio\n",
    "ads and newspaper ads constant. The hypotheses for radio and newspaper are similar.  The p-values for TV and radio are both very low, suggesting that the null hypotheses\n",
    "are false. We can reject the null hypotheses in favour of the alternative hypothesis, that there is an impact of TV (and radio) advertising on sales. However, the high p-value of newspaper does not allow us to reject the null hypothesis that newspaper has no effect on sales. We cannot conclude that it has an effect on sales, and we cannot conclude that it does not.\n",
    "\n",
    "## (ISLR #3) [25 marks]\n",
    "\n",
    "$$\\hat Y = 50 + 20 GPA + 0.07 IQ + 35 Gender + 0.01(GPA \\times IQ) - 10 (GPA \\times Gender) $$\n",
    "\n",
    "a) **[5 marks]** The coefficient for gender $\\hat\\beta_3$ is positive , but the interaction between $Gender$ and $IQ$ is negative. So for sufficiently high values of $GPA$, the interaction term will be large (and negative), so males will earn less (on average) than females.\n",
    "\n",
    "Note: This difference in salary can be calculated directly. For fixed values of $IQ=x_1$ and $GPA=x_2$\n",
    "\n",
    "\\begin{align}\\hat {Salary}_\\text{male} &=50 + 20 x_1 + 0.07 x_2 + 0.01(x_1 x_2)\\\\\n",
    "\\hat {Salary}_\\text{female} &=50 + 20 x_1 + 0.07 x_2 + 35 + 0.01(x_1 x_2) - 10 x_1 \\end{align}\n",
    "\n",
    "$$\\hat {Salary}_\\text{male} - \\hat {Salary}_\\text{female} = 35 - 10 x_1$$\n",
    "\n",
    "b) **[5 marks]** When $Gender = 1, IQ = 110, GPA = 4.0 $\n",
    "\n",
    "\\begin{align} \\hat Y &= 50 + 20 * 4 + 0.07 * 110 + 35 + 0.01 (4 * 110) - 10 * 4 \\\\\n",
    "&= 137.1 \\end{align}\n",
    "\n",
    "(c) **[10 marks]** \n",
    "\n",
    "**[5]** False. The magnitude of the coefficient depends on the scale of the predictor. To assess whether there is statistical evidence of relationship beteen the predictor and the response, we must examine the p-value of the test-statistic. This statistic *scales* the coefficient by the standard error (it puts each coefficient on a standard scale) so that they can be compared.\n",
    "\n",
    "**[5]** The reason that the coefficeints on interaction terms tehd to be small is because they are two predictors *multiplied* together. So the values of these predictors ($X_1 \\times X_2$) tend to be larger than than the indivudal predictors $X_1$ and $X_2$. This means the coefficients (e.g. $\\hat\\beta_4$) will tend to be smaller than $\\hat \\beta_1$ and $\\hat \\beta_2$.\n",
    "\n",
    "## (ISLR #6) [25 marks]\n",
    "The regression line is given by:\n",
    "\\begin{array}\n",
    "yy = \\hat\\beta_0 + \\hat\\beta_1 x\n",
    "\\end{array}\n",
    "\n",
    "From 3.4, we know that $\\hat\\beta_0 = \\bar y - \\hat\\beta_1 \\bar x$. Subbing in this term:\n",
    "\n",
    "\\begin{array}\n",
    "yy &= (\\bar y - \\hat\\beta_1 \\bar x) + \\hat\\beta_1 x \\\\\n",
    "0 &= \\bar y - y - \\hat\\beta_1 \\bar x + \\hat\\beta_1 x \\\\\n",
    "\\end{array}\n",
    "\n",
    "For the right hand side to equal zero, $(\\bar{y},\\bar{x})$ must be points on this regression line (i.e. $y = \\bar{y}$ and $x = \\bar{x}$).\n",
    "\n",
    "## (ISLR #8) [25 marks]\n",
    "\n",
    "### 8 a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "      mpg          cylinders      displacement     horsepower        weight    \n",
       " Min.   : 9.00   Min.   :3.000   Min.   : 68.0   Min.   : 46.0   Min.   :1613  \n",
       " 1st Qu.:17.00   1st Qu.:4.000   1st Qu.:105.0   1st Qu.: 75.0   1st Qu.:2225  \n",
       " Median :22.75   Median :4.000   Median :151.0   Median : 93.5   Median :2804  \n",
       " Mean   :23.45   Mean   :5.472   Mean   :194.4   Mean   :104.5   Mean   :2978  \n",
       " 3rd Qu.:29.00   3rd Qu.:8.000   3rd Qu.:275.8   3rd Qu.:126.0   3rd Qu.:3615  \n",
       " Max.   :46.60   Max.   :8.000   Max.   :455.0   Max.   :230.0   Max.   :5140  \n",
       "                                                                               \n",
       "  acceleration        year           origin                      name    \n",
       " Min.   : 8.00   Min.   :70.00   Min.   :1.000   amc matador       :  5  \n",
       " 1st Qu.:13.78   1st Qu.:73.00   1st Qu.:1.000   ford pinto        :  5  \n",
       " Median :15.50   Median :76.00   Median :1.000   toyota corolla    :  5  \n",
       " Mean   :15.54   Mean   :75.98   Mean   :1.577   amc gremlin       :  4  \n",
       " 3rd Qu.:17.02   3rd Qu.:79.00   3rd Qu.:2.000   amc hornet        :  4  \n",
       " Max.   :24.80   Max.   :82.00   Max.   :3.000   chevrolet chevette:  4  \n",
       "                                                 (Other)           :365  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Auto <- read.table(\"~/rotman/RSM8512/Data/Auto.data.txt\", header= TRUE,na.strings=\"?\") #load data into a data frame. NOTE THE FUNCTION CHANGED BECAUSE DIFFERENT DATA FORMAT!\n",
    "Auto = na.omit(Auto)\n",
    "attach(Auto)\n",
    "\n",
    "summary(Auto)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = mpg ~ horsepower)\n",
       "\n",
       "Residuals:\n",
       "     Min       1Q   Median       3Q      Max \n",
       "-13.5710  -3.2592  -0.3435   2.7630  16.9240 \n",
       "\n",
       "Coefficients:\n",
       "             Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept) 39.935861   0.717499   55.66   <2e-16 ***\n",
       "horsepower  -0.157845   0.006446  -24.49   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 4.906 on 390 degrees of freedom\n",
       "Multiple R-squared:  0.6059,\tAdjusted R-squared:  0.6049 \n",
       "F-statistic: 599.7 on 1 and 390 DF,  p-value: < 2.2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lm.fit = lm(mpg ~ horsepower)\n",
    "summary(lm.fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "i) [5 marks] We can reject the null hypothesis of no relationship because the p-value on the (single) predictor is very small. Becuase there is only one predictor, this is equivalent to the F-test which tests if any of the predictors is associated with the response. (note the p-values are the same).\n",
    "\n",
    "ii) [5 marks] A change in horsepower of one unit leads to a change in mpg of -.158. Over the range of horsepower $(230-46)=184$, this would yield a change in mpg of $184*(-.158)=-29.1$ which is 29/37.6 = 77% of the range of mpg in the data. This is a strong relationship between horsepower and mpg. The R^2 of this regression is 0.605, so 60.6% of the variance in mpg is captured by horsepower.\n",
    "\n",
    "iii) [2 marks] The relatinship is negative. As horsepower increases, mpg decreases.\n",
    "\n",
    "iv) [3 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>fit</th><th scope=col>lwr</th><th scope=col>upr</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>24.46708</td><td>23.97308</td><td>24.96108</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       "  & fit & lwr & upr\\\\\n",
       "\\hline\n",
       "\t1 & 24.46708 & 23.97308 & 24.96108\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | fit | lwr | upr | \n",
       "|---|\n",
       "| 1 | 24.46708 | 23.97308 | 24.96108 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  fit      lwr      upr     \n",
       "1 24.46708 23.97308 24.96108"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict(lm.fit, data.frame(horsepower=c(98)), interval=\"confidence\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>fit</th><th scope=col>lwr</th><th scope=col>upr</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>24.46708</td><td>14.8094 </td><td>34.12476</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       "  & fit & lwr & upr\\\\\n",
       "\\hline\n",
       "\t1 & 24.46708 & 14.8094  & 34.12476\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | fit | lwr | upr | \n",
       "|---|\n",
       "| 1 | 24.46708 | 14.8094  | 34.12476 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  fit      lwr     upr     \n",
       "1 24.46708 14.8094 34.12476"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict(lm.fit, data.frame(horsepower=c(98)), interval=\"prediction\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8b\n",
    "[5 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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MYo9HEOzT/6IUQiQad8XGkhNfjS+/N9yNXMVkJ/kciZNFuYTePTek2Ov7s5zbDX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KGXQQL/8VbsZ8wj7rcRlRc6cZliZOTeau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\n",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(horsepower, mpg)\n",
    "abline(lm.fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8c "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAAAEJCcBO7hoaG/Pz8mpoa6CwGAAAA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\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09Pz169ejF5TEdHUlNTs379emdnZ3Nz\nc3d399jY2I5Yml1fX9/JyWn//v2ShdnZ2cXFxQ1Xm2AupzV8Moienl51dbWsQmr4NukmhkDc\nuXNn3bp1MTEx2dnZhJC6ujp7e/s5c+Y8ePDg/fv3qamprq6uc+bMmThxYlZW1vDhw+/fv//m\nzZsVK1bcv3/fwsJCVgHDBweTJwBUULPX9OLj4zU1NZ8/f97xlw/lBLdim3Xz5k0NDQ0Oh9On\nTx83NzdmePXChQu7dOkyfPjwe/fu1dXV5efnL1q0iMvlXr9+veMiKSsr69u3r6Wl5YYNGw4f\nPrxixQp9ff0xY8Z0xP2jlJQULpcbEhJy+/bt3Nzc/fv3d+7c2d3dncPhJCUlsZuVlpba2tqq\nqanVWzS5vLxcV1c3MTFRJsHk5eVRFPXrr7+yJWKxeOnSpRRFOTg4TJo0iTlRYWFhvac0e3h4\n+Pn5URT173//m9lRJBIFBAQQQhISEmQSW9vgVqz8NXsrFgBkTuG3YptP7MRisbOzc2hoqByi\nkQ8kds0yMzPT09MrKChgS5illiwsLJiF6llBQUGjRo3quEiioqJ69Ojx9u1btiQnJ0dPT2//\n/v0dcbpff/3V2dmZyZB4PF50dHR1dfWqVavU1NSmTp26efPmL7/8UiAQODo6zp49u2vXrnfv\n3mV2LCkpmTBhQvfu3WtqamQVTGBgoJGRUUhIyJEjR168eOHk5ERRVN++fbds2RIaGqqpqRkU\nFGRqasrlcrdu3SoSid69excREUFRFIfD8fT0rHc0AwODfv36ySq2NkBiJ39KmNjdu3fPyclJ\nX1+fz+cPGDDg999/V3READL2ASR2NE0/evQoOTm5o0ORGyR20j179owQsm3bNslCoVBIUVTv\n3r3rbfzzzz/r6+t3XDD29vYxMTH1CufPn+/n59dxJy0vL3/+/LnkU4J//fXXwMDATz75xNvb\n+9tvv33//n11dXVgYKCampqTk9OQIUN4PF6fPn1k+FsqPj7eyMhIS0uLvRFMUdRnn332/v17\nZoPffvuNeZZevdknERERhJAlS5bUO+DAgQNNTExkFV4bILGTP2WbPLFp0yaKonR0dLy8vIYP\nH858vdlLy9IlJCR4enqamJgYGBg4Ozvv2bNHKBS2Mx7yv/OlJ35JCAAAIABJREFUZCUzM5MQ\nwsyFaskpYmNjJf92hQ+dwhO75sfYEUJsbW1Hjhwpixu/8AF4+PAhIWT48OGSherq6urq6pJz\nCxhcLpd9KF1HKCkpafgwjs6dO3fo9As9PT0rKyvJoXXu7u7x8fF37tw5e/ZseHg4l8vV0tKK\nj49PS0ubMWPGiBEjDhw4cPfuXTs7u6aOWV1dPWvWLFtb2549e/r5+b169UpKANeuXQsODo6M\njKyoqHj16tWZM2cEAgFFUbNnz2ZHRPXp08fa2prD4TBPG2atWrWKEHLjxo16x3z79q22tnZr\nmwJUW2ZmZnl5uXzOVVVVFRkZ2bdv34qKipSUlIsXL1ZUVPTq1evzzz9///699H3/9re/BQQE\nmJmZrVixYtmyZXw+PyQkJDw8vCPizMrKajistg2YjjEyMrLZuSmhoaFFRUXtPyMAo0WJHXxU\nmCVK680DJYSIxeKqqqp6I/qTk5OdnJw6LpguXbowS1NIevTokbW1dcedtOWcnZ0jIiJWrlw5\nfvx4KU9Rvn79uqGh4YEDB2pqaiiKOnXqlKWlZb2JGpK2bdvm5+e3dOlSdXV1ExOTUaNGaWlp\nOTo6bt++XXIzZiXARo9w+/ZtyWkcd+7cefr0qbe3d+vfIqgyeU6eiI2NFYlEp0+fZpdaUVdX\nP3HihFAoPHjwoJQdb926tWPHjvPnzx86dGjx4sVffvnluXPn1qxZ89133zGr/CknJrHbsGGD\nQCBQdCzwcUFiB/XZ2Njo6elFRkbW1dWxhYsXL2buLMycOfPNmzeEkLq6us2bN+/atYtZxr6D\nTJs2bfv27Y8ePWJLLly48NNPP02fPr3jTipzPj4+2traT58+zcvLe/LkSXFxsbW1dUhISEVF\nRaPbP3z40MPDQ7LEzMxMIBA8ePBAstDQ0JCm6dOnT0sWrlu3jhDy/v17gUDwxRdfxMbGBgQE\nuLi46Ovr18sLAeS58kROTk7Dp2H36tWLoqgnT55I2XHVqlXz58/39PSULAwPDx88eHBGRgZb\ncuTIkf79+/N4vAEDBhw5ckRyYylVDJFIFBwcbGBgcPfuXVNTU3aFvdzcXH9/f4FAwOPxmHlj\nTQUZGxtrb29vaGg4bty4wsJCQgjTf1IUxf5p2ujRmKuDtra27GXC4uLi8PBwOzs7bW1tgUAw\nbty4x48fM1UURd2/f3/ZsmV9+/bV1dX19PSU/Lv32LFjAwYM4PF4Li4u8fHxbHl2draPj4+h\noaGZmVlQUBAzdx5UmQJvAysKxtg16+eff6YoSltb29/fPyQkhLmG5+vre/PmzT59+qirq3fr\n1k1bW9vY2LiDJjGwhELhlClTNDQ0goKCli9fPnbsWDU1tcjIyA49qWxdvnyZEHLs2DHJwoKC\nAkLI+vXrG92lX79+mzZtkizZtGmTrq6uk5MTW/Lw4UNdXV19fX0NDQ128sSSJUsoinJzc8vI\nyGB+ZRJC1NXVP/30U4UP4sEYO/lTqskTmzZtIoQUFRVJFjJPDoqNjZWyo4mJyc2bN6UfPCEh\ngaKo8PDwI0eOhIeHUxR19OjRZqsIIZmZmSKRKCQkhMfjsc8Dnzx5Mk3TYrHYxsbG09Nzx44d\ne/bsGTVqVJcuXSSfIs46cOAAISQsLOzAgQPTp0/X19cnhJSVldESY+yaOlpeXh4hJCUlJS8v\nj6bpuro6W1tbHo+3dOnSw4cPb9q0qX///ux/fEKIs7Pz3LlzT58+HR8f36NHDxcXF6bq5MmT\n6urqX3755dGjR+fNm0cI+f7772maLigo4PP506dPP3z48ObNm83NzQ0MDJ4+fSq9PaE9FD7G\nDokdNO7BgwcODg6amprq6uqmpqY7duxgyoVC4ZUrV77//vuzZ88yPZccnDhxYu7cuSNGjFiw\nYEFaWpp8TiormzdvJv8ZSS2pU6dOAQEBje7y+eefDxw4UHJUe2VlJY/H09DQCA8P37Zt24IF\nCzQ1NQMCAv7444/evXuT//zdTwgZOnRobW0tu2N5eXlHvKk2QGInf62ePOHkRBPy339cLi2Z\nUbW7VkjIAltbtkwkEjF/KEp+Y+thFjJ+8+aN9Hfq4OAg2auvXLmyb9++zVYRQh49erRo0SJt\nbe2rV6+y21RXV9M0nZ+fTwhhF3qpqqqaO3duo38g2djYLFu2jPlZLBb7+/uzMbOJnZSjEYkJ\nFsXFxcOGDdu3bx978Fu3blEUxQY8d+5ctur8+fMcDof5uX///mvXrmWrvLy8hg4dStP04sWL\nFyxYwJY/e/ZMR0cnMDBQSmNCOyGxUwAkdiBPzD2RejPjmFnG4eHhje7yxx9/GBsbjxo16saN\nG2VlZWlpaV5eXmZmZlu3bvXx8XFwcJgwYcJPP/3Ebp+enr569eqNGzc+fvy4Y99MOyCxk79m\nE7tLly79T8704AF9/vx//128SP9nFrZMag/NnduJEH19fV9fXx8fHx6PR1HU1q1bpUTITDMq\nLS2Vsg0znDQnJ4ctyc7OpiiqpqZGShVN04SQCRMmEEIcHBwazrGtqakRCAQeHh6JiYlSAqiq\nqiKESF4DO3nyJCHk1atXtETSJuVoDfsHRklJyfnz55k0kd3ywoUL7AbM9Fvm4BRFSb7Nqqoq\n5pO1t7e/fPmy5GHHjh1raWnZ1NuB9kNi16TKysqcnJy3b99KPnVCJpDYgTzV1taqqam5ublJ\nFs6ZM6ep3pzx+PFjybkOPj4+H/rdEyR28tdsYnft2rWKigq5xcOckRk9pqOj4+DgcPv2benb\ni8ViQ0PDeosmM2JiYphVy5m7mZKP2GTyuby8PClVNE0TQvT19Tds2EAIaTS/fPTo0ZQpU3R1\ndSmKGjp0aKO3Cxqe4u7du+zFOcn/5k0drV5X8OzZMz8/P3NzcxMTk08//XTGjBmSid2jR4/Y\nLdnErmEMrEbnwmtqajbcEmQFiV19N27cmDhxop6eHvsV1NbWnjx58rVr12R1CiR2IGfMI0g6\nd+78t7/9bcWKFcxTUZhxPNK9ffv2/v37crvl3aGQ2MmfUo2xa7Phw4cvXLiwXmFZWRmXy50z\nZw7d2BU7ZuhedXW1lCqapgkhZ86coWma+aXz8uXLRgN4//799evXJ02aZGBg0DB5evfuXb0r\ndqdOnSKE5Ofn041djWt4NMltxGJx9+7dw8LCMjIymIsazNQxprbe0djE7s8//ySESC4QlZub\ne+nSJZqmzczMjh49mtlAU60N7afwxE65ZsWeOXPG1dXVwMAgKSmpqKiotra2qKjowoUL5ubm\nw4cPP3funKIDBGiLNWvWHD16VCgUxsTErF+//sWLF5s2bTp69GizO/L5fEdHR2YsNsDHKSws\nbNeuXfVmf2/atEkoFE6aNIkQoqWlZW9v/8MPP7C1+/fvd3Bw0NLSklLFvOzatSshZMuWLXV1\ndV9++aXkKYqLi7t3715RUcHlct3c3Hbu3Pn27dvS0tJ64Wlqavbp02fPnj1sCXM6yacKtPxo\nL1++zMnJ+frrr/v27csMnL19+3azTaStrW1ra3v48GG2ZNGiRcuXLyeE9OvX7/79+zb/YWVl\n9cUXX0jOmQXV0+STtxRi1apVISEhu3fvZktMTU1NTU1dXV11dHTWrFmD5yTDB2ry5MmTJ09W\ndBQA/+P169dGRkZqamqKDkSayZMnJycn+/r6Tp482dXV9d27dxcvXkxNTZ05c+aYMWOYbVat\nWhUYGFhRUeHq6pqWlrZ169aEhIRmq1hWVlYrV66MiooKDQ0dMmQIU2hsbKyuru7n5xccHEzT\ndHx8vJ2dnbm5ecMIo6KigoKCKisr3dzckpOTmVSs3pPbpRyNy+UmJCR4eHgMHTpUIBAIBIKQ\nkJCAgAANDY3k5OTExERCSFJSkvTnUEZHR0+fPr2srKx///4XL15MSkpisrfo6Gh3d/f8/Hxv\nb+/CwsL4+PisrKy1a9e2/nOAD4cCrxY2pKure/DgwUarzpw5w+PxZHIW3IoFkD/cipW/Vk+e\nUFZisfjAgQPu7u4GBgZGRkZubm5xcXH1ZpofPnzYyclJR0fHyckpISGhJVVE4s5mTU1N7969\nHRwc3kvM+Xj48OGIESP4fD4z4SM7O7upCPfs2WNnZ8fn88eMGcNMgGVmMkmeoqmjRUZG6urq\nGhgYMC+vXbvWv39/LS0tGxubiIiIsrIyb29vPp/PzNJo9FYs4+DBg46Ojtra2g4ODnFxcWz5\n5cuX3d3ddXV1TU1Nx48ff+vWrZa0ObSZwm/FUnQTT65XiIEDBzo5Oe3atath1d///vdLly5d\nv369/WfhcDgrV65cs2ZN+w8FAC30z3/+8+jRozdv3lR0IB8RHo93+PBhX1/fpja4fv16nz59\n5PaMYoCPga+v76VLl5hEXCGU61bsP/7xjzFjxojF4tmzZ/fs2ZPP55eVleXk5Bw6dGjXrl3H\njx9XdIAAAKpj0KBBig4BAGRMuSZPjBo1Ki0t7c2bN97e3gKBQENDQyAQeHp6FhYWXrx4cfTo\n0YoOEAAAAEB5KdcVO0KIi4sLM1a0oqKipKTE0NBQX1+ffao+AADIygcxeQIAWkW5rthJ0tPT\n69atG5/PR1YHANARMjMzy8vLFR0FAMiS8iZ2AADQobhcLpfLVXQUACBLH0xiN2rUqJZfuhs4\ncCDVNJqmi4uLOzRaAADlN2jQIEyJBVAxSjfGrimxsbHMqiktERcXV1hY2FTt2LFj8aBjAAAA\nUD0fTGLXpUuXlm9sZ2fHLMfZKHV1dXX1D+aNAwB0EEyeAFA9ynsrtqqqKjc3l1n+XNGxAACo\nIEyeAFA9SpfY3bx5c9KkSfr6+jwer3v37gYGBrq6uv7+/jJZcwIAAFiYPAGgepQrsTtz5oyr\nq6uBgUFSUlJRUVFtbW1RUdGFCxfMzc2HDx9+7tw5RQcIAKA6MHkCQPUo11CzVatWhYSE7N69\nmy0xNTU1NTV1dXXV0dFZs2YNJj0AAAAANEW5rthlZWUNGzas0aphw4Y9ePBAzvEAAKiw169f\ni0QiRUcBALKkXFfsbG1tr1y5Mm3atIZVV65ccXBwkNWJnj59eufOnXYe5Pbt2zo6OjKJp/3K\ny8u1tbWVZLhMbW1tbW2tnp6eogMhhBCapktKSkxMTBQdyF+Ki4uNjY2VZD2VysrKHj16GBoa\nyuFcL168kMNZoB7pfV15efmbN29qa2vlGVKj3r59y+PxlOF5BZWVlVwuV1NTU9GBkJqamrq6\nOl1dXUUHQurq6iorKw0MDBQdCKFp+s2bN8bGxooOhBBCKisrBw4c2LBc8ROSaGVy5swZiqJC\nQkKuXbv2+vXr9+/fv379Oi0tbdGiRVwuNykpSSZn6dq1q4IbHeCjNHr0aJn8F4YWarav+/HH\nH3v37i2XDx/gI2JiYqLA//jKldjRNJ2enu7n5yf5N4qWltbEiROvXr2q6ND+R3V1NSEkPT1d\n0YH8ZdCgQevXr1d0FH9ZuXKll5eXoqP4S2pqKlGmP2DU1NRSUlIUHcVfvL29o6KiFB0FKEyn\nTp3Onj2r6Chomqbt7Ox27Nih6ChomqbHjh27ZMkSRUdB0zQdHh7u5+en6Chomqa3bt3at29f\nRUdB0zR96tQpHR0dRUdB0zT96NEjQkhRUZGiA2mE4q971+Pi4pKYmEgIqaioKCkpMTQ01NfX\nV5L7VgAAAADKTOkSO5aenp6SDNICAAAA+CAo16xYAAAAAGgzJHYAAAAAKgKJHQAAAICKQGIH\nAAAAoCKQ2AEAAACoCCR2AAAAACpCeR93ouS4XG7nzp2NjIwUHchfLCwszM3NFR3FX8zNzS0s\nLBQdxV+MjY2tra0VHcV/WVtbK8/6Zubm5srztQH5s7KyUpJvo6WlpZmZmaKjIESZ/lOYm5sL\nhUJFR0EIIWZmZpaWloqOghBCBAKBlZWVoqMghBA+n29ubq48y4pKomiaVnQMAAAAACADuBUL\nAAAAoCKQ2AEAAACoCCR2AAAAACoCiR0AAACAikBiBwAAAKAikNgBAAAAqAgkdgAAAAAqAokd\nAAAAgIpAYgcAAACgIpDYAQAAAKgIJHYAAAAAKgKJHQAAAICKQGIHAAAAoCKQ2LXauXPnqP81\nYcIEhUQyYMCArKyseoXJyckuLi48Hs/Z2fns2bMKDEb+DSUSiWJiYgYPHqynp2dtbb1s2bJ3\n796xtfJvGSnxyL9xzp8/P3jwYD6fb2ZmFhwc/OrVK8laRX1tQFZa/glK2bJtVUpLJm3CUKrO\ntp3a3yzK1tO2X/vbRLk6WBpaKSYmRktLa4uEEydOyDmGd+/effPNN4SQzMxMyfL09HSKokJD\nQw8cOBASEkJR1I0bNxQVjPwbavny5YSQGTNmHD58+JtvvjExMQkLC2OqFNIyUuKRc+PcuXOH\nw+EMGzZs796933//vZ2d3YgRI9hahTQOyFDLP0EpW7atSmnJpE1oJets208mzaJsPW07tb9N\nlK2DRWLXanPmzBkyZIgCA1i2bBmXy2Xy8np9jZ+fX0hICPtyzpw5EydOVFQwcm4ooVCoq6sb\nGBjIlqSmpnK53JqaGloRLSM9Hjk3zrx58wQCQW1tLfMyMzOTEFJeXs68lH/jgGy1/BOUsmXb\nqpSWTNpEqTpbmWh/syhbT9t+7W8TZetgkdi12sCBA52dnQcMGKClpWVjY7NlyxaRSCTPAAoK\nCh48ePDgwYOGfY2uru61a9fYl1evXtXT01NUMHJuqKKiot69eyckJLAlhYWFhJD8/HxaES0j\nPR45N84333zz9ddfsy9fvnxJCCktLWVeyr9xQLZa/glK2bJtVUpLJm2iVJ2tTLS/WZStp22/\n9reJsnWwSOxaRyQS6erqGhsb79u37+bNm9u2bePxeBs2bFBIMPX6mvLyckLI69ev2ZKioiJC\nSGVlpfyDUXhDicXiZcuW9ezZUyQSKbZlGsajwMa5f//+sWPHRo0aNWbMGKZEGRoH2qPln6CU\nLdtW1WHvqb1k0iaSmylVZ9tmMm8WWvl62taSbZsoSQeLxK51hEJhampqQUEBWxIXF8fn88Vi\nsfyDqdfX5OTkEELev3/PltTW1hJCcnJy5B+MYhuqoKAgMDBQT08vLS2NVnTLNIxHgY1jaWlJ\nCOFwOP/617+EQiGtBI0D7dTyT1DKlm2r6rD31F4yaRPJzZSqs20zmTeLsvW0bSDbNlGSDhaz\nYltHXV3dw8OD+fAYPj4+ZWVlzLVoxTI0NCSElJWVsSXMz0y5nCmqoWpqaqKjo3v27FlbW/vg\nwQNXV1ei0JZpNB4Ffovy8/PLy8svX778ww8/zJkzhyjZ1wbaoOWfoJQt21Yl8/ciKzJpE5kc\nX6nIsFmUradtM9l+VZSkg0Vi1zoFBQUpKSlCoZAtoWmaEKKvr6+4oP6ir6+vpaWVm5vLluTm\n5mprayskNoU01MuXL/v375+QkJCamvrzzz9bWVkx5YpqmabikXPj0DQdFxf322+/EUIoitLT\n0xs8eHBMTExiYiJRsq8NtEHLP0EpW7atqsPeU3vJpE1kcnylIqtmUbaetj3a3yZ6enrK1sEi\nsWudZ8+ejRgx4ujRo2zJTz/9ZGdnp6urq8CoGBRFjR49+tChQ2xJfHz86NGjKYqSfzDybyia\npv39/Q0NDW/fvu3i4iJZpZCWkRKPnBuHoqjo6OjVq1dLFj58+NDa2poo2dcG2qDln6CULdtW\n1WHvqb1k0iYyOb5SkUmzKFtP207tbxMOh6NsHax6xx1aJbm7u48ePXr+/Pm5ubk9e/a8devW\n9u3bJX9DK1ZERISnpyePxxsyZMiVK1d27dqVmpqqkEjk31AZGRnXrl2bPn16bGysZHlwcLCh\noaH8W0ZKPPJvnIULF0ZGRs6dO3fEiBF1dXVpaWl79uxhA1Oerw20jZRPMD8/PzQ0lH0mqpQt\n21altGTSJm07vjJrf7MoW0/bfu1vE6XrYDtu+J6qEgqF0dHRjo6OOjo6AwYMOHnypKIiIQ1m\n4NM0nZSUxDzh2tXV9ezZswoMRs4NdfDgwUa/4WxUcm4Z6fHIuXFEItHWrVuHDRvG5/ONjY2H\nDRtW74yK+tqArDT1CTKP1GrJlm2uUloyaROGUnW27dTOZlG2nlYm2tkmytbBUjRNtz87BAAA\nAACFwxg7AAAAABWBxA4AAABARSCxAwAAAFARSOwAAAAAVAQSOwAAAAAVgcQOAAAAQEUgsQMA\nAABQEUjsAAAAAFQEEjsAAAAAFYHEDgAAAEBFILEDAAAAUBFI7AAAAABUBBI7AAAAABWBxA4A\nAABARSCxAwAAAFARSOwAAAAAVAQSOwAAAAAVgcQOAAAAQEUgsQMAAABQEUjsAAAAAFQEEjsA\nAAAAFYHEDgAAAEBFILEDAAAAUBFI7AAAAABUBBI7AAAAABWBxA4AAABARSCxAwAAAFARSOyg\npagmMFVZWVnMZnv27CkrK2P3qvey5bKysiiKEovFsgqejRAAoJ3QpYDSUld0APAhOXDgQKPl\nkZGRhoaGzM+hoaGDBw/m8/mNvmwtkUjE4eDPDwAAgBZBYgetMH369EbLN2zY0EFnFIlEXC63\ngw4OAACgYnAtBGSAvSvB3Jm1tbVlb9FKvmRkZ2f7+PgYGhqamZkFBQVlZ2ezVbGxsfb29oaG\nhuPGjSssLCSE1NXV1TvX1KlTu3btStM0WzJ58uSuXbuKxeLi4uLw8HA7OzttbW2BQDBu3LjH\njx9LiZbB3PNtNrzc3Fx/f3+BQMDj8YYPH37v3r02NxcAqLZGuxEpfVdTuxBCKIrKyMiYPn26\nqakpUyK9ozty5Ei/fv2MjIwCAgLS09Nb2PeCKkFiB7KUl5dHCElJSWF+qPeSEPLixYuBAwca\nGhp+9913kZGRly5dcnFxycnJIYQcPHhw3rx5w4YN27Ztm76+/sSJEwkhIpGo3immTJny/Plz\nNq+qqqo6ffp0cHAwTdPDhg3bt2+fr6/v3r17IyMjCwsLAwMDWxV/U+HRNO3j41NaWrp69epv\nv/1WU1Nz/Pjxshr/BwCqpKlupKm+i8PhSOkYCSERERElJSX/93//RwgRiURSOrqTJ09Omzbt\n008//e6773R0dAICApqNSr5tA3JBA7RMo9+fzMxMpor5od7PDV8uXrx4wYIF7Mtnz57p6OgE\nBgbSNG1jY7Ns2TKmXCwW+/v7E0LevHlTL4zq6mpdXd3ly5czLw8fPkwIyc7OLi4uZvo7dstb\nt25RFNUwjHohZWZmsv8RmgovPz+fEFJYWMiUV1VVzZ079+3bt61pPwBQHfW6EUlNdSNN9V1S\ndmFO5OfnJxaLmSrpHd2AAQNWr17NVk2bNq3Zzq3NLQBKC4kdtBTTkdVTU1NDtyaxs7e3v3z5\nsuRhx44da2lpWVVVRQh5+vQpW37y5ElCyKtXrxpGEhQUZGtry/zs5+c3aNCgehuUlJScP3+e\nSQ0bhiElsWsqvJqaGoFA4OHhkZiYWFpa2lxTAYCKk5LYNdWN0E33XVJ2IYScPHmy0RPV6+hq\namooimLuMDBOnTrVbOfW0jcMHw5MnoBWsLGxaecR8vLyhg0bVq9QU1OzuLiYEGJpackWMj83\nvBVLCJkyZUp8fPzjx48tLCySkpK2bdvGlD9//jwiIiI9Pb2urs7R0dHc3LwlIdESFyObCq9T\np06XLl1avXp1cHDwn3/+OWTIkI0bN7q6urbk+ADwUWmqGyFN911SdiGEdO3aVbK8qY7u5cuX\nNE1bWFiwW0r+LP0UoEqQ2IFc6enp7d+/38HBoV65mZkZIeTFixfdu3dnSpjJE40mdt7e3np6\neomJidbW1oSQKVOmEEJomvby8ho5cuTZs2f79OlDUVRmZmZTz2eRxJxIeniEEFtb2yNHjgiF\nwtu3b8fExIwZM6awsBDdIgDUI6UbabTvkr4LIURd/b+/qaV0dMzsiqKiIjYRfPXqVUuiAhWD\nyRMgV/369bt//77Nf1hZWX3xxRfx8fGampp9+vTZs2cPu+UPP/xAGpsVSwjR1NScMGFCYmJi\nQkLC+PHjmYfkvXz5Micn5+uvv+7bty8zEez27duNxsDhcIqKitiXR44caTa84uLi7t27V1RU\ncLlcNze3nTt3vn37trS0VEatAgCqo6luhDTRd0nfpR4pHZ2WlpadnZ3kX7PMML7WngI+dLhi\nBzLG5XITEhI8PDyGDh3a8GV0dLS7u3t+fr63t3dhYWF8fHxWVtbatWsJIVFRUUFBQZWVlW5u\nbsnJyUxv1egVO0LIlClTfH19MzIyfvnlF6ZEIBAIBIKQkJCAgAANDY3k5OTExERCSFJSkre3\nt+S+n3zySVhY2Jo1a3g8XmJi4t27d9mqpsIzNjZWV1f38/Njpt/Gx8fb2dm18FYvAKikEydO\nNPzrcfr06VJ6OdJY30Wkdoz1SO/ooqOjAwMDKysrBwwYkJKSkp6ezl7ta/kp4IOn0BF+8CGR\n8m0hEuOIIyMjdXV1DQwMGn1J0/Tly5fd3d11dXVNTU3Hjx9/69YttmrPnj12dnZ8Pn/MmDHM\nRNTHjx83esba2lo+n29qaioUCtnCa9eu9e/fX0tLy8bGJiIioqyszNvbm8/nMzMz2Ah///33\noUOHamtr29jYREZGPnjwQPKtNRXew4cPR4wYwefz9fX1fX19mblsAPBxkv4rVUov12jfJWUX\n0mCWhpSOjqbpffv29e7d28TEZNasWVeuXBEIBM2eAlQMRTf9BQUAAIAPRXZ2toWFhY6ODvPy\n7NmzERERzMR/+HhgjB0AAIAqCAwM3LdvH/vy7NmzgwYNUmA8oBAYYwcAAKAKZs+evWLFCm1t\nbXt7+/Pnz+/cufPq1auKDgrkDYkdAACAKggLC6uqqlq3bl1xcbGjo+OpU6cGDhyo6KBA3jDG\nDgAAAEBFYIwdAAAAgIpAYgcAAACgIpDYAQAAAKgIJHYAAAAAKgKJHQAAAICKQGIHAAAAoCKQ\n2AEAAACoCCR2AAAAACoCiR0AAACAikBiBwAAAKAikNgd//kcAAAAWUlEQVQBAAAAqAgkdgAA\nAAAqAokdAAAAgIpAYgcAAACgIpDYAQAAAKgIJHYAAAAAKgKJHQAAAICKQGIHAAAAoCKQ2AEA\nAACoCCR2AAAAACoCiR0AAACAivh/OIJyW1Jz4voAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "par(mfrow=c(2,2))\n",
    "plot(lm.fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[5 marks] There appears to be some non-linearity in the data. In the plotn of rediduals vs. fitted values, we observe tha the residuals are high both when the fitted values are very low and when they are very high. If the model was truly linear, we would expect no pattern on the residuals (they should be mean zero noise). \n",
    "\n",
    "We had not yet covered the remaining plots (so are not counted for marks):\n",
    "Similar results can be seen in the QQ plot (residuals vs. quantiles) where the residuals are larger then expected in the lower and upper quantiles, and the form the leverage plot. For all of the high leverage observations, the residuals are higher than expected. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## (ISLR #11) [25 marks]\n",
    "\n",
    "## 11 a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = y ~ x + 0)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-1.9154 -0.6472 -0.1771  0.5056  2.3109 \n",
       "\n",
       "Coefficients:\n",
       "  Estimate Std. Error t value Pr(>|t|)    \n",
       "x   1.9939     0.1065   18.73   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 0.9586 on 99 degrees of freedom\n",
       "Multiple R-squared:  0.7798,\tAdjusted R-squared:  0.7776 \n",
       "F-statistic: 350.7 on 1 and 99 DF,  p-value: < 2.2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set.seed(1)\n",
    "x=rnorm(100)\n",
    "y=2*x+rnorm(100)\n",
    "\n",
    "lm.fit = lm(y~x+0)\n",
    "summary(lm.fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**[5 marks]** The coefficient is 1.9939, which is very close to the true value of 2. We can reject the null that the coefficient is zero (the p-value is small). The t-stat is 18.73 and the p-value is $<2\\times 10^{-16}$\n",
    "\n",
    "We cannot reject the null that it is 2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<strong>x:</strong> -0.0575141308601551"
      ],
      "text/latex": [
       "\\textbf{x:} -0.0575141308601551"
      ],
      "text/markdown": [
       "**x:** -0.0575141308601551"
      ],
      "text/plain": [
       "          x \n",
       "-0.05751413 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<strong>x:</strong> 0.954251575328252"
      ],
      "text/latex": [
       "\\textbf{x:} 0.954251575328252"
      ],
      "text/markdown": [
       "**x:** 0.954251575328252"
      ],
      "text/plain": [
       "        x \n",
       "0.9542516 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t= (coef(lm.fit) - 2) / summary(lm.fit)$coef[2]\n",
    "t # test statistic\n",
    "2*(1-pt(abs(t),100-1)) # p-value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 11 b "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = x ~ y + 0)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-0.8699 -0.2368  0.1030  0.2858  0.8938 \n",
       "\n",
       "Coefficients:\n",
       "  Estimate Std. Error t value Pr(>|t|)    \n",
       "y  0.39111    0.02089   18.73   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 0.4246 on 99 degrees of freedom\n",
       "Multiple R-squared:  0.7798,\tAdjusted R-squared:  0.7776 \n",
       "F-statistic: 350.7 on 1 and 99 DF,  p-value: < 2.2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lm.fit = lm(x~y+0)\n",
    "summary(lm.fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**[5 marks]** The coefficient is 0.391, and it is significantly different than zero. The t-stat is 18.73.\n",
    "\n",
    "## 11 c\n",
    "\n",
    "**[5 marks]** \n",
    "\n",
    "The data generating process $y=2x+\\epsilon$ can be re-written as: \n",
    "\n",
    "$$x=.5y - .5 \\epsilon$$\n",
    "\n",
    "The second regression is estimating this model. However there is an issue here, because now the error term in the model is correlated with the predictor ($y$ and  $\\epsilon$ are correlated). \n",
    "\n",
    "Because they are positively correlated, our estiamte of the coefficient from the second regression will be too small (0.39 vs 0.5).\n",
    "\n",
    "To see this, we can reject the null that it is 0.5. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<strong>y:</strong> -5.2132603327398"
      ],
      "text/latex": [
       "\\textbf{y:} -5.2132603327398"
      ],
      "text/markdown": [
       "**y:** -5.2132603327398"
      ],
      "text/plain": [
       "       y \n",
       "-5.21326 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<strong>y:</strong> 1.01664961982273e-06"
      ],
      "text/latex": [
       "\\textbf{y:} 1.01664961982273e-06"
      ],
      "text/markdown": [
       "**y:** 1.01664961982273e-06"
      ],
      "text/plain": [
       "          y \n",
       "1.01665e-06 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t= (coef(lm.fit) - 0.5) / summary(lm.fit)$coef[2]\n",
    "t # test statistic\n",
    "2*(1-pt(abs(t),100-1)) # p-value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The p-value for the null of 0.5 is very small. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even so, the test-statistic for the null of zero is the same in both regressions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 11d.\n",
    "\n",
    "**[5 marks]**\n",
    "The t-statistic is given by:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$ t = \\frac{\\hat\\beta}{SE(\\hat\\beta)} $$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this problem, there is only one predictor $x$ and no intercept, so OLS estimation is given by:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\begin{array}{cc}\n",
    "\\hat\\beta = \\frac {x^\\top y} {x^\\top x} \\quad \\text{and } SE(\\hat\\beta) = \\sqrt{\\frac {\\hat\\sigma} {x^\\top x}}, \\text{ and } \\hat\\sigma = \\frac {e^\\top e} {(n-1)}\n",
    "\\end{array}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution using linear algebra"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because there is only one predictor, $x^\\top x = \\sum_{i=1}^n x_i^2$ is just a scalar (a number). This means we can write the inverse as division i.e. $(x^\\top x)^{-1} = \\frac{1}{x^\\top x}$. This is only true for the case of one predictor."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So the t-statistic is given by:\n",
    "\n",
    "\\begin{array}\n",
    " tt &= \\frac {x ^\\top y} {x^\\top x} \\sqrt{\\frac {(n-1) x^\\top x} {e^\\top e}} \\\\\n",
    " & = \\frac { \\sqrt{n-1} \\ x ^\\top y} {\\sqrt{x^\\top x \\ e ^\\top e}}\n",
    "\\end{array}\n",
    "\n",
    "The term in the denominator $x^\\top x \\ e ^\\top e$ needs to be expanded\n",
    "\n",
    "\\begin{array}\n",
    "xx^\\top x \\ e ^\\top e &= x^\\top x \\left( \\ (y-x\\hat\\beta) ^\\top (y-x\\hat\\beta) \\right)\\\\\n",
    "&= x^\\top x \\left( \\ y^\\top y -2 \\hat\\beta x^\\top y +\\hat\\beta^2 x^\\top x  \\right)\\\\\n",
    "&= x^\\top x \\left( \\ y^\\top y -2 \\hat\\beta x^\\top y +\\hat\\beta x^\\top y  \\right)\\\\\n",
    "&= x^\\top x \\left( \\ y^\\top y - \\hat\\beta x^\\top y \\right)\\\\\n",
    "&= x^\\top x \\ y^\\top y - \\hat\\beta x^\\top x \\ x^\\top y \\\\\n",
    "&= x^\\top x \\ y^\\top y - x^\\top y \\ x^\\top y \\\\\n",
    "\\end{array}\n",
    "\n",
    "The third and fifth line come from recognizing that $x^\\top x \\ \\hat \\beta = x^\\top y$.\n",
    "\n",
    "Putting all of these terms together yields:\n",
    "\n",
    "\\begin{array}\n",
    " tt = \\frac { \\sqrt{n-1} \\ x ^\\top y} {\\sqrt{x^\\top x \\ y^\\top y - x^\\top y \\ x^\\top y}}\n",
    "\\end{array}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution using standard algebra\n",
    "\n",
    "\\begin{array}\n",
    "tt&={\\frac {\\sum{x_i y_i}} {\\sum{x_i^2}}}\n",
    "    {\\sqrt{\\frac {(n-1) \\sum{x_i^2}} {\\sum{(y_i - x_i \\beta)^2}}}}\\\\\n",
    "    &=\\frac {\\sqrt{n-1} \\sum{x_i y_i}}\n",
    "      {\\sqrt{\\sum{x_i^2} \\sum{(y_i - x_i \\beta)^2}}} \\\\\n",
    "&=\\frac {\\sqrt{n-1} \\sum{x_i y_i}}\n",
    "      {\\sqrt{\\sum{x_i^2} \\sum{(y_i^2 - 2 \\beta x_i y_i  + x_i^2 \\beta^2)}}} \\\\\n",
    "&=\\frac {\\sqrt{n-1} \\sum{x_i y_i}}\n",
    "      {\\sqrt{\\sum{x_i^2} \\sum{y_i^2} - \n",
    "            \\sum{x_i^2} \\beta (2 \\sum{x_i y_i} - \\beta \\sum{x_i^2})}} \\\\\n",
    "&=\\frac {\\sqrt{n-1} \\sum{x_i y_i}}\n",
    "      {\\sqrt{\\sum{x_i^2} \\sum{y_i^2} - \n",
    "            \\sum{x_i y_i} (2 \\sum{x_i y_i} - \\sum{x_i y_i})}} \\\\\n",
    "&= \\frac {\\sqrt{n-1} \\sum{x_i y_i}} \n",
    "          {\\sqrt{\\sum{x_i^2} \\sum{y_i^2} - (\\sum{x_i y_i})^2 }}\n",
    "          \\end{array}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
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     "data": {
      "text/html": [
       "18.7259319374486"
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       "18.7259319374486"
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       "18.7259319374486"
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       "[1] 18.72593"
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   "source": [
    "(sqrt(length(x)-1) * sum(x*y)) / (sqrt(sum(x*x) * sum(y*y) - (sum(x*y))^2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 11 e\n",
    "\n",
    "**[3 marks]** In the formula for the test statistic in 11d, ASSUMING THAT $y$ IS UNCORRELATED WITH $\\epsilon$, we can replace $y$ with $x$ and get the same answer."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 11 f\n",
    "**[2 marks]**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = y ~ x)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-1.8768 -0.6138 -0.1395  0.5394  2.3462 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept) -0.03769    0.09699  -0.389    0.698    \n",
       "x            1.99894    0.10773  18.556   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 0.9628 on 98 degrees of freedom\n",
       "Multiple R-squared:  0.7784,\tAdjusted R-squared:  0.7762 \n",
       "F-statistic: 344.3 on 1 and 98 DF,  p-value: < 2.2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = x ~ y)\n",
       "\n",
       "Residuals:\n",
       "     Min       1Q   Median       3Q      Max \n",
       "-0.90848 -0.28101  0.06274  0.24570  0.85736 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  0.03880    0.04266    0.91    0.365    \n",
       "y            0.38942    0.02099   18.56   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 0.4249 on 98 degrees of freedom\n",
       "Multiple R-squared:  0.7784,\tAdjusted R-squared:  0.7762 \n",
       "F-statistic: 344.3 on 1 and 98 DF,  p-value: < 2.2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lm.fit = lm(y~x)\n",
    "lm.fit2 = lm(x~y)\n",
    "summary(lm.fit)\n",
    "summary(lm.fit2)"
   ]
  }
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