StatsDemo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Programmer: Johnny L. Hopkins\n",
    "# Date: June 27, 2019\n",
    "# Revised: June 29, 2019\n",
    "# Revised: July 1, 2019\n",
    "# Revised: July 7, 2019\n",
    "# Revised: July 8, 2019\n",
    "# Demonstrates the statistics module\n",
    "# by calculating descriptive statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean is 61.75\n",
      "The median is 77.5\n",
      "The mode is 80\n",
      "The sample variance is 884.5\n",
      "The population variance is 773.9375\n",
      "The sample standard deviation is 29.740544715926102\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# To use the statistics module, import into your program\n",
    "import statistics\n",
    "\n",
    "# I will create a histogram of my_list \n",
    "# using matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# This expression will allow the histogram\n",
    "# to appear after running the program\n",
    "%matplotlib inline\n",
    "\n",
    "# The statistics module works on lists\n",
    "# Lists will be explained later in the series\n",
    "my_list = [25, 35, 75, 80, 80, 89, 90, 20]\n",
    "\n",
    "# First, we will find the mean\n",
    "my_list_mean = statistics.mean(my_list)\n",
    "\n",
    "# The print statement outputs input to the screen\n",
    "print(\"The mean is\", my_list_mean) \n",
    "\n",
    "# Next, we find the median\n",
    "# If the data set has an odd number of elements, \n",
    "# the median is the middle value of the list. \n",
    "# However, if the list has an even number of elements, \n",
    "# The median is computed by taking the two middle elements \n",
    "# and divide them by two. To simplify the process, order\n",
    "# the list elements from the smallest to the largest. \n",
    "my_list_median = statistics.median(my_list)\n",
    "print(\"The median is\", my_list_median) \n",
    "\n",
    "# The mode is the element that appears the most\n",
    "# in the list. Every list has at least one mode.\n",
    "# The example list has no mode, so statistics.mode()\n",
    "# should return a StatisticsError because the list\n",
    "# has equally common values. \n",
    "my_list_mode = statistics.mode(my_list)\n",
    "print(\"The mode is\", my_list_mode) \n",
    "\n",
    "# The variance measures the spread of a distribution \n",
    "# of data. There are two types of variance: The sample \n",
    "# and population variance. The sample variance is a measure \n",
    "# of a sample and the population variance looks at the spread of the \n",
    "# data for the population. The statistics module provides methods for\n",
    "# both the population and sample variance. \n",
    "my_list_svariance = statistics.variance(my_list) \n",
    "print(\"The sample variance is\", my_list_svariance) \n",
    "\n",
    "my_list_popvariance = statistics.pvariance(my_list) \n",
    "print(\"The population variance is\", my_list_popvariance) \n",
    "\n",
    "# The standard deviation is defined mathematically \n",
    "# as the square root of the variance. Specifically, it is \n",
    "# it quantifies the spread or dispersion of a distribution. \n",
    "# The statistics module provides methods for the population \n",
    "# sample standard deviation. \n",
    "my_list_sstdev = statistics.stdev(my_list)\n",
    "print(\"The sample standard deviation is\", my_list_sstdev)\n",
    "\n",
    "# We plot the histogram and display it\n",
    "# to the notebook\n",
    "plt.hist(my_list, bins = 10)\n",
    "plt.title('StatsDemo Histogram')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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