{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sampling distributions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We consider real estate data from the city of Ames, Iowa. The details of every real estate transaction in Ames is recorded by the City Assessor's office. Our particular focus for this lab will be all residential home sales in Ames between 2006 and 2010. This collection represents our population of interest. In this lab we would like to learn about these home sales by taking smaller samples from the full population."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import io\n",
    "import requests\n",
    "\n",
    "df_url = 'https://raw.githubusercontent.com/akmand/datasets/master/openintro/ames.csv'\n",
    "url_content = requests.get(df_url, verify=False).content\n",
    "ames = pd.read_csv(io.StringIO(url_content.decode('utf-8')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order</th>\n",
       "      <th>PID</th>\n",
       "      <th>MS.SubClass</th>\n",
       "      <th>MS.Zoning</th>\n",
       "      <th>Lot.Frontage</th>\n",
       "      <th>Lot.Area</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>Lot.Shape</th>\n",
       "      <th>Land.Contour</th>\n",
       "      <th>...</th>\n",
       "      <th>Pool.Area</th>\n",
       "      <th>Pool.QC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>Misc.Feature</th>\n",
       "      <th>Misc.Val</th>\n",
       "      <th>Mo.Sold</th>\n",
       "      <th>Yr.Sold</th>\n",
       "      <th>Sale.Type</th>\n",
       "      <th>Sale.Condition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>526301100</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>141.0</td>\n",
       "      <td>31770</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>215000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>526350040</td>\n",
       "      <td>20</td>\n",
       "      <td>RH</td>\n",
       "      <td>80.0</td>\n",
       "      <td>11622</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>105000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>526351010</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>81.0</td>\n",
       "      <td>14267</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gar2</td>\n",
       "      <td>12500</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>172000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>526353030</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>93.0</td>\n",
       "      <td>11160</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>244000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>527105010</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>74.0</td>\n",
       "      <td>13830</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>189900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 82 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Order        PID  MS.SubClass MS.Zoning  Lot.Frontage  Lot.Area Street  \\\n",
       "0      1  526301100           20        RL         141.0     31770   Pave   \n",
       "1      2  526350040           20        RH          80.0     11622   Pave   \n",
       "2      3  526351010           20        RL          81.0     14267   Pave   \n",
       "3      4  526353030           20        RL          93.0     11160   Pave   \n",
       "4      5  527105010           60        RL          74.0     13830   Pave   \n",
       "\n",
       "  Alley Lot.Shape Land.Contour  ... Pool.Area Pool.QC  Fence Misc.Feature  \\\n",
       "0   NaN       IR1          Lvl  ...         0     NaN    NaN          NaN   \n",
       "1   NaN       Reg          Lvl  ...         0     NaN  MnPrv          NaN   \n",
       "2   NaN       IR1          Lvl  ...         0     NaN    NaN         Gar2   \n",
       "3   NaN       Reg          Lvl  ...         0     NaN    NaN          NaN   \n",
       "4   NaN       IR1          Lvl  ...         0     NaN  MnPrv          NaN   \n",
       "\n",
       "  Misc.Val Mo.Sold Yr.Sold Sale.Type  Sale.Condition  SalePrice  \n",
       "0        0       5    2010       WD           Normal     215000  \n",
       "1        0       6    2010       WD           Normal     105000  \n",
       "2    12500       6    2010       WD           Normal     172000  \n",
       "3        0       4    2010       WD           Normal     244000  \n",
       "4        0       3    2010       WD           Normal     189900  \n",
       "\n",
       "[5 rows x 82 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ames.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  For this lab, we'll restrict our attention to just two of the variables: the above ground living area of the house in square feet (Gr.Liv.Area) and the sale price (SalePrice)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "area = ames['Gr.Liv.Area']\n",
    "price = ames['SalePrice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2930.000000\n",
       "mean     1499.690444\n",
       "std       505.508887\n",
       "min       334.000000\n",
       "25%      1126.000000\n",
       "50%      1442.000000\n",
       "75%      1742.750000\n",
       "max      5642.000000\n",
       "Name: Gr.Liv.Area, dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "area.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histogram of areas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 302,
       "width": 604
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline \n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "plt.style.use('ggplot')\n",
    "plt.rcParams['figure.figsize'] = (10,5)\n",
    "\n",
    "plt.hist(area, edgecolor = 'black', linewidth = 1.2)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 1: Test the distribution of areas by making a Q-Q plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 335,
       "width": 620
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.stats import probplot\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "probplot(area, plot = plt)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The unknown sampling distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "sampl1 = area.sample(50) #we collect a simple random sample (size 50) from the vector area."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 2: Make a Q-Q plot for the random sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 335,
       "width": 620
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "probplot(sampl1, plot = plt)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1346.9"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sampl1.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 3: Take two more samples, one of size 100 and one of size 1000. Which would you think would provide a more accurate estimate of the population mean?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "sampl2 = area.sample(100)\n",
    "sampl3 = area.sample(1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1601.83\n",
      "1513.945\n"
     ]
    }
   ],
   "source": [
    "print(sampl2.mean())\n",
    "print(sampl3.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Not surprisingly, every time we take another random sample, we get a different sample mean. It's useful to get a sense of just how much variability we should expect when estimating the population mean this way. The distribution of sample means, called the sampling distribution, can help us understand this variability. In this lab, because we have access to the population, we can build up the sampling distribution for the sample mean by repeating the above steps many times. Here we will generate 5000 samples and compute the sample mean of each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 302,
       "width": 604
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_means50 = [area.sample(50).mean() for i in range(0, 5000)]\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (10,5)\n",
    "plt.hist(sample_means50, edgecolor = 'black', linewidth = 1.2)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 302,
       "width": 598
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = (10,5)\n",
    "plt.hist(sample_means50, edgecolor = 'black', linewidth = 1.2, bins = 25)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 4: Make a Q-Q plot for sample_means50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 335,
       "width": 620
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "probplot(sample_means50, plot = plt)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sample size and the sampling distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The sampling distribution that we computed tells us much about estimating the average living area in homes in Ames. Because the sample mean is an unbiased estimator, the sampling distribution is centered at the true average living area of the the population, and the spread of the distribution indicates how much variability is induced by sampling only 50 home sales."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### To get a sense of the effect that sample size has on our distribution, let's build up two more sampling distributions: one based on a sample size of 10 and another based on a sample size of 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_means10 = [area.sample(10).mean() for i in range(0, 5000)]\n",
    "sample_means100 = [area.sample(100).mean() for i in range(0, 5000)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 319,
       "width": 598
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 319,
       "width": 598
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 319,
       "width": 598
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = (10,5)\n",
    "plt.hist(sample_means10, edgecolor = 'black', linewidth = 1.2, bins = 25, color = 'blue')\n",
    "plt.title(\"sample size of 10\")\n",
    "plt.show();\n",
    "plt.hist(sample_means50, edgecolor = 'black', linewidth = 1.2, bins = 25)\n",
    "plt.title(\"sample size of 50\")\n",
    "plt.show();\n",
    "plt.hist(sample_means100, edgecolor = 'black', linewidth = 1.2, bins = 25, color = 'purple')\n",
    "plt.title(\"sample size of 100\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 5: When the sample size is larger, what happens to the center? What about the spread?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1496.43408\n",
      "1500.330984\n",
      "1499.133736\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(sample_means10))\n",
    "print(np.mean(sample_means50))\n",
    "print(np.mean(sample_means100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "158.22312208572296\n",
      "70.03213773455543\n",
      "49.62293339134945\n"
     ]
    }
   ],
   "source": [
    "print(np.std(sample_means10))\n",
    "print(np.std(sample_means50))\n",
    "print(np.std(sample_means100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 6: Make the same proccess for prices"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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