Data Science: An Introduction/Thinking Like a Programmer

 Data Science: An Introduction  Chapter 08: Thinking Like a Programmer



Note to Contributors (remove this section when the chapter is complete)
First, please register yourself with Wikibooks (and list yourself below), so that we know who our co-contributors are. Also, please abide by the Wikibooks Editing Guidelines, Manual of Style, and Policies and Guidelines. Thank you.

Secondly, we only need basic, clear, straightforward information in each chapter. We are not trying to be exhaustive or complete—the value of this book is in the simple synthesis across subjects. There are other venues in which to wax eloquent on the deepness and complexities of a particular subject. Please place yourself in a "beginner's mind" as you make contributions. Please also scope each chapter so that it can be taught in a one-hour class period. If the chapter requires more than an hour to teach, it is probably too detailed.
 * To the extent possible, please use terms and concepts in the way in which they are defined in the Wikipedia and Wiktionary. This way students can refer to the corresponding Wikipedia / Wiktionary page to get a deeper understanding of the concept.

Thirdly, this is a cross-disciplinary book. We want to help people apply data science to all fields. Therefore, we need a wide variety of simple examples and simple exercises.

Fourthly, please adhere to the simple structure of each chapter: Summary of Main Points, Discussion, More Reading, Exercises, and References. We want the More Reading section to link to on-line resources. The References section may contain off-line resources. To start a new page, you should use the wiki markup from this prototype page.

Fifthly, as with any Wikibook please feel free to make corrections, expand explanations, and make additions where necessary, even if it is not "your" chapter. Use the discussion page to explain changes that might be controversial.

Sixthly, some syntax rules:


 * Please bold key terms and phrases the student should learn.
 * Put the name of functions and code snippets using the 'code' tags:
 * Use in-line links  to the Wikipedia, Wiktionary, WikiCommons, Wikibooks, and other Wikimedia Foundation properties.
 * Use references to "external" sources—both on-line and off-line.
 * Use the citations templates to make citations : Template:Cite book, Template:Cite web, Template:Cite journal
 * If you want to add an image or graph, you should load it into the Commons rather than uploading into Wikibooks.
 * If appropriate, add the tag ) when you upload the graph.
 * If using a different package than R standard packages, put the name of the package in bold in parenthesis after each function : (MCMCpack)
 * You can use the third chapter Definitions of Data as an example of how to craft a chapter.

Finally, thank you so much for volunteering to be part of our our team!

Assignment/Exercise
This Project #1, which spans two chapters. Assemble into groups of 3 or 4 students. This group will do the entire project together. Note: Your group can specialize on tasks, but everyone needs to participate in all phases of the assignment. Also, the chapters covered to this point do not teach you everything you need to know to do this assignment. Please do the best you can with what you know. This assignment is not just to show the instructor how much of the previous chapters you have learned, but the assignment is a learning experience in and of itself. The assignment is designed for the students to discover knowledge not contained in the chapters.
 * 1) As a group look at several data sets on the Census website.  Collectively choose one table and download it.  Choose a subset of the table to analyze.
 * 2) Enter the data into R.  Use R to produce tables and draw plots of your data.  Identify any interesting results.
 * 3) Prepare a slide presentation that includes a description of your methods, a table of your results, a graph or plot of your results, significant findings, and a list of several things the group learned on its own about data science during the course of this project.

Copyright Notice


You are free: Under the following conditions:
 * to Share — to copy, distribute, display, and perform the work (pages from this wiki)
 * to Remix — to adapt or make derivative works
 * Attribution — You must attribute this work to Wikibooks. You may not suggest that Wikibooks, in any way, endorses you or your use of this work.
 * Share Alike — If you alter, transform, or build upon this work, you may distribute the resulting work only under the same or similar license to this one.
 * Waiver — Any of the above conditions can be waived if you get permission from the copyright holder.
 * Public Domain — Where the work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license.
 * Other Rights — In no way are any of the following rights affected by the license:
 * Your fair dealing or fair use rights, or other applicable copyright exceptions and limitations;
 * The author's moral rights;
 * Rights other persons may have either in the work itself or in how the work is used, such as publicity or privacy rights.


 * Notice — For any reuse or distribution, you must make clear to others the license terms of this work.The best way to do this is with a link to the following web page.
 * http://creativecommons.org/licenses/by-nc-sa/3.0/