Day1/One way ANOVA .ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  BAD Day 1: One way ANOVA \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook is intended to demonstrate the application of the one way ANOVA analysis on a built in R data set: **PlantGrowth**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>weight</th><th scope=col>group</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>4.17</td><td>ctrl</td></tr>\n",
       "\t<tr><td>5.58</td><td>ctrl</td></tr>\n",
       "\t<tr><td>5.18</td><td>ctrl</td></tr>\n",
       "\t<tr><td>6.11</td><td>ctrl</td></tr>\n",
       "\t<tr><td>4.50</td><td>ctrl</td></tr>\n",
       "\t<tr><td>4.61</td><td>ctrl</td></tr>\n",
       "\t<tr><td>5.17</td><td>ctrl</td></tr>\n",
       "\t<tr><td>4.53</td><td>ctrl</td></tr>\n",
       "\t<tr><td>5.33</td><td>ctrl</td></tr>\n",
       "\t<tr><td>5.14</td><td>ctrl</td></tr>\n",
       "\t<tr><td>4.81</td><td>trt1</td></tr>\n",
       "\t<tr><td>4.17</td><td>trt1</td></tr>\n",
       "\t<tr><td>4.41</td><td>trt1</td></tr>\n",
       "\t<tr><td>3.59</td><td>trt1</td></tr>\n",
       "\t<tr><td>5.87</td><td>trt1</td></tr>\n",
       "\t<tr><td>3.83</td><td>trt1</td></tr>\n",
       "\t<tr><td>6.03</td><td>trt1</td></tr>\n",
       "\t<tr><td>4.89</td><td>trt1</td></tr>\n",
       "\t<tr><td>4.32</td><td>trt1</td></tr>\n",
       "\t<tr><td>4.69</td><td>trt1</td></tr>\n",
       "\t<tr><td>6.31</td><td>trt2</td></tr>\n",
       "\t<tr><td>5.12</td><td>trt2</td></tr>\n",
       "\t<tr><td>5.54</td><td>trt2</td></tr>\n",
       "\t<tr><td>5.50</td><td>trt2</td></tr>\n",
       "\t<tr><td>5.37</td><td>trt2</td></tr>\n",
       "\t<tr><td>5.29</td><td>trt2</td></tr>\n",
       "\t<tr><td>4.92</td><td>trt2</td></tr>\n",
       "\t<tr><td>6.15</td><td>trt2</td></tr>\n",
       "\t<tr><td>5.80</td><td>trt2</td></tr>\n",
       "\t<tr><td>5.26</td><td>trt2</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " weight & group\\\\\n",
       "\\hline\n",
       "\t 4.17 & ctrl\\\\\n",
       "\t 5.58 & ctrl\\\\\n",
       "\t 5.18 & ctrl\\\\\n",
       "\t 6.11 & ctrl\\\\\n",
       "\t 4.50 & ctrl\\\\\n",
       "\t 4.61 & ctrl\\\\\n",
       "\t 5.17 & ctrl\\\\\n",
       "\t 4.53 & ctrl\\\\\n",
       "\t 5.33 & ctrl\\\\\n",
       "\t 5.14 & ctrl\\\\\n",
       "\t 4.81 & trt1\\\\\n",
       "\t 4.17 & trt1\\\\\n",
       "\t 4.41 & trt1\\\\\n",
       "\t 3.59 & trt1\\\\\n",
       "\t 5.87 & trt1\\\\\n",
       "\t 3.83 & trt1\\\\\n",
       "\t 6.03 & trt1\\\\\n",
       "\t 4.89 & trt1\\\\\n",
       "\t 4.32 & trt1\\\\\n",
       "\t 4.69 & trt1\\\\\n",
       "\t 6.31 & trt2\\\\\n",
       "\t 5.12 & trt2\\\\\n",
       "\t 5.54 & trt2\\\\\n",
       "\t 5.50 & trt2\\\\\n",
       "\t 5.37 & trt2\\\\\n",
       "\t 5.29 & trt2\\\\\n",
       "\t 4.92 & trt2\\\\\n",
       "\t 6.15 & trt2\\\\\n",
       "\t 5.80 & trt2\\\\\n",
       "\t 5.26 & trt2\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "weight | group | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 4.17 | ctrl | \n",
       "| 5.58 | ctrl | \n",
       "| 5.18 | ctrl | \n",
       "| 6.11 | ctrl | \n",
       "| 4.50 | ctrl | \n",
       "| 4.61 | ctrl | \n",
       "| 5.17 | ctrl | \n",
       "| 4.53 | ctrl | \n",
       "| 5.33 | ctrl | \n",
       "| 5.14 | ctrl | \n",
       "| 4.81 | trt1 | \n",
       "| 4.17 | trt1 | \n",
       "| 4.41 | trt1 | \n",
       "| 3.59 | trt1 | \n",
       "| 5.87 | trt1 | \n",
       "| 3.83 | trt1 | \n",
       "| 6.03 | trt1 | \n",
       "| 4.89 | trt1 | \n",
       "| 4.32 | trt1 | \n",
       "| 4.69 | trt1 | \n",
       "| 6.31 | trt2 | \n",
       "| 5.12 | trt2 | \n",
       "| 5.54 | trt2 | \n",
       "| 5.50 | trt2 | \n",
       "| 5.37 | trt2 | \n",
       "| 5.29 | trt2 | \n",
       "| 4.92 | trt2 | \n",
       "| 6.15 | trt2 | \n",
       "| 5.80 | trt2 | \n",
       "| 5.26 | trt2 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "   weight group\n",
       "1  4.17   ctrl \n",
       "2  5.58   ctrl \n",
       "3  5.18   ctrl \n",
       "4  6.11   ctrl \n",
       "5  4.50   ctrl \n",
       "6  4.61   ctrl \n",
       "7  5.17   ctrl \n",
       "8  4.53   ctrl \n",
       "9  5.33   ctrl \n",
       "10 5.14   ctrl \n",
       "11 4.81   trt1 \n",
       "12 4.17   trt1 \n",
       "13 4.41   trt1 \n",
       "14 3.59   trt1 \n",
       "15 5.87   trt1 \n",
       "16 3.83   trt1 \n",
       "17 6.03   trt1 \n",
       "18 4.89   trt1 \n",
       "19 4.32   trt1 \n",
       "20 4.69   trt1 \n",
       "21 6.31   trt2 \n",
       "22 5.12   trt2 \n",
       "23 5.54   trt2 \n",
       "24 5.50   trt2 \n",
       "25 5.37   trt2 \n",
       "26 5.29   trt2 \n",
       "27 4.92   trt2 \n",
       "28 6.15   trt2 \n",
       "29 5.80   trt2 \n",
       "30 5.26   trt2 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Getting the data set and having a peek into its content\n",
    "help(PlantGrowth)\n",
    "PlantGrowth"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will now use the `summary` functon to get more information about the whole data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     weight       group   \n",
       " Min.   :3.590   ctrl:10  \n",
       " 1st Qu.:4.550   trt1:10  \n",
       " Median :5.155   trt2:10  \n",
       " Mean   :5.073            \n",
       " 3rd Qu.:5.530            \n",
       " Max.   :6.310            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Getting a basic summary of the data\n",
    "summary(PlantGrowth)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also get statistical information on a single attribute of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "0.701191842508168"
      ],
      "text/latex": [
       "0.701191842508168"
      ],
      "text/markdown": [
       "0.701191842508168"
      ],
      "text/plain": [
       "[1] 0.7011918"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Computing the SD of a given attribute \n",
    "sd(PlantGrowth$weight)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or per groups within the data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>ctrl</dt>\n",
       "\t\t<dd>0.583091378392406</dd>\n",
       "\t<dt>trt1</dt>\n",
       "\t\t<dd>0.793675696434703</dd>\n",
       "\t<dt>trt2</dt>\n",
       "\t\t<dd>0.442573283322786</dd>\n",
       "</dl>\n"
      ],
      "text/plain": [
       "     ctrl      trt1      trt2 \n",
       "0.5830914 0.7936757 0.4425733 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute the sd of each group for the given attribute\n",
    "tapply(PlantGrowth$weight, PlantGrowth$group, sd)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next thing we will do is creating a boxplot of the data set (as in the main Tutorial)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LLAZencBU3uoL4R2KiAAmmjcl5HgAAB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\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "boxplot(weight ~ group, data =  PlantGrowth, col = 'mediumpurple', \n",
    "        xlab = 'Group', ylab = 'Weight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also create histograms of the data. In this case we will use the lattice plotting system:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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768T8VXmjp0EE8iQIAAAQIECNSIgFeQ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\nRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Creating a conditional histogram of the data\n",
    "par(mfrow =  c(1,3))\n",
    "\n",
    "# We will use the lattice plotting system \n",
    "library(lattice)\n",
    "\n",
    "# Creating the histogram\n",
    "histogram(~weight | group, data =  PlantGrowth, col = 'mediumpurple', type = 'count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** Our  null hypotesis is that the three groups have the same growth mean**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we will use a completely randomized design one-way ANOVA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            Df Sum Sq Mean Sq F value Pr(>F)  \n",
       "group        2  3.766  1.8832   4.846 0.0159 *\n",
       "Residuals   27 10.492  0.3886                 \n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# One way ANOVA (Randomized design)\n",
    "analysis <- aov(weight ~ group, data = PlantGrowth)\n",
    "summary(analysis)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will build a linear model with `lm()` and will then use the `anova()` command to analyse the fit "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>group</th><td> 2        </td><td> 3.76634  </td><td>1.8831700 </td><td>4.846088  </td><td>0.01590996</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>27        </td><td>10.49209  </td><td>0.3885959 </td><td>      NA  </td><td>        NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tgroup &  2         &  3.76634   & 1.8831700  & 4.846088   & 0.01590996\\\\\n",
       "\tResiduals & 27         & 10.49209   & 0.3885959  &       NA   &         NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | Df | Sum Sq | Mean Sq | F value | Pr(>F) | \n",
       "|---|---|\n",
       "| group |  2         |  3.76634   | 1.8831700  | 4.846088   | 0.01590996 | \n",
       "| Residuals | 27         | 10.49209   | 0.3885959  |       NA   |         NA | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "          Df Sum Sq   Mean Sq   F value  Pr(>F)    \n",
       "group      2  3.76634 1.8831700 4.846088 0.01590996\n",
       "Residuals 27 10.49209 0.3885959       NA         NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit <- lm(weight ~ group, data = PlantGrowth)\n",
    "anova(fit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As expected, both approaches provide the same results!"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.3.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}