{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "###
San Jose State University
Department of Applied Data Science

**DATA 200
Computational Programming for Data Analytics**

Spring 2024
Instructor: Ron Mak
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 3.17 Intro to Data Science: Measures of Central Tendencyâ€”Mean, Median and Mode " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **Measures of central tendency** in descriptive statistics:\n", "- **mean**: the *average* of a set of values\n", "- **median**: the *middle value* of a set of **sorted** values\n", "- **mode**: the *most frequently occuring* value in a set of values\n", "\n", "#### Each is a single value that represents a \"central\" value of the set of values, one that is most \"typical\" of the values." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "grades = [85, 93, 45, 89, 85]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(f'mean = {sum(grades)/len(grades)}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Recall the `min()` and `max()` functions:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(f'min = {min(grades)}')\n", "print(f'max = {max(grades)}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### The statistics module of the Standard Python Library has functions to calculate the mean, median, and mode of a list of values." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import statistics" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(f'mean = {statistics.mean(grades)}')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(f'sorted grades = {sorted(grades)}')\n", "print(f'median = {statistics.median(grades)}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### What if there are an even number of values in the list? Then the median is the average of the two middle values." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "even_list = [86, 14, 55, 92, 75, 80]\n", "\n", "print(f'sorted grades = {sorted(even_list)}')\n", "print(f'median = {statistics.median(even_list)}')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(f'mode = {statistics.mode(grades)}')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "##########################################################################\n", "# (C) Copyright 2019 by Deitel & Associates, Inc. and #\n", "# Pearson Education, Inc. All Rights Reserved. #\n", "# #\n", "# DISCLAIMER: The authors and publisher of this book have used their #\n", "# best efforts in preparing the book. These efforts include the #\n", "# development, research, and testing of the theories and programs #\n", "# to determine their effectiveness. The authors and publisher make #\n", "# no warranty of any kind, expressed or implied, with regard to these #\n", "# programs or to the documentation contained in these books. The authors #\n", "# and publisher shall not be liable in any event for incidental or #\n", "# consequential damages in connection with, or arising out of, the #\n", "# furnishing, performance, or use of these programs. #\n", "##########################################################################\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Additional material (C) Copyright 2023 by Ronald Mak" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 4 }