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A Survivor's Guide to R An Introduction for the Uninitiated and the Unnerved

Handbook / Manual
By: Kurt Taylor Gaubatz(Author)
384 pages
A Survivor's Guide to R
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  • A Survivor's Guide to R ISBN: 9781483346731 Paperback Jun 2014 Not in stock: Usually dispatched within 1-2 months
Price: £54.00
About this book Contents Customer reviews Related titles

About this book

A Survivor's Guide to R provides a gentle, but thorough, introduction to R. It is an ideal supplement to any introductory statistics text or a practical field guide for those who want to use the powerful R language for statistical analysis in their own research. A Survivor's Guide to R focuses on providing students with the real-world R skills that are often hard to get to in statistics classes: basic data management and manipulation, and working with R graphics. A Survivor's Guide to R is designed to get students with little or no background in statistics or programming started on R within the context of a statistics class, and to ensure that they have acquired functional R skills that they can continue to use as they move on to their own projects.

A Survivor's Guide to R begins with a straightforward approach to understanding R objects, and then moves systematically through the use of R to transform, sort, and aggregate data; to work with complex textual and date/time data; and to effectively build on R's default graphics capabilities to produce highly customized and effective graphics. It focuses on working with real-world data, with – on reading data in different formats and the challenges of missing data. A Survivor's Guide to R is intended for those with little to no statistics or programming experience – students and other new users who are likely to find their first encounter with R more than a little intimidating. It is written in an accessible and sympathetic style that makes minimal assumptions about user skills, and provides frequent warnings about common pitfalls that must be avoided along the road to R mastery. .


Chapter 1: Getting Started     
Things Your Statistics Class Probably Won't Teach You     
Why R?     
Statistical Modeling     
A Few R Basics     
Saving Your Work     
R Packages     
Help with R Help     
Organization of this Book     

Chapter 2: A Sample Session     
Reviewing Your Data     
Data Visualization     
Hypothesis Testing for Fun and Profit     
A Regression Model     
A Nonlinear Model     

Chapter 3: Object Types in R     
R Objects And Their Names     
How to Think about Data Objects in R     
R Object Storage Modes     
R Data Object Types     
The Basic Data Objects: Vectors     
The Basic Data Objects: Matrices and Their Indices     
The Basic Data Objects: Data Frames     
The Basic Data Objects: Lists     
A Few Things about Working with Objects     
Object Attributes     
Objects and Environments     
R Object Classes     
The Pseudo Storage Modes     
Date and Time as a Storage Modes     
Coercing Storage Modes     
The Curse of Number-Character-Factor Confusion     

Chapter 4: Getting Your Data Into R     
Entering Data     
Creating Data     
Importing Data     
The Read Command: Overview     
The Read Command: Reading from the Clipboard     
The Read Command: Blank Delimited Tables     
The Read Command: Comma Separated Values     
The Read Command: Tab Separated Data     
The Read Command: Fixed-Width Data     
Importing Foreign File Types     
Integrating SQL with R     
Extracting Data from Complex Data Sources     
Web Scraping     
Dealing with Multi-Dimensional Data     
Importing Problematic Characters     
More Resources     

Chapter 5: Reviewing and Summarizing Data     
Summary Functions     
Checking A Sample Of Your Data     
Reviewing Data By Categories     
Displaying Data With A Histogram     
Displaying Data With A Scatter Plot     
Scatter Plot Matrices     

Chapter 6: Sorting and Selecting Data     
Using Index Values to Select Data     
Using Conditional Values for Selecting     
Using Subset( ) with Variable or Row Names to Select Data     
Splitting a Dataset into Groups     
Splitting Up Continuous Numeric Data     
Sorting And Ordering Data     

Chapter 7: Transforming Data     
Creating New Variables     
Editing Data     
Basic Math with R     
R Functions     
Math and Logical Functions in R     
Truncation and Rounding Functions     
The Apply( ) Family of Functions     
Changing Variable Values Conditionally     
Creating New Functions     
Additional R Programming     
Character Strings as Program Elements and Program Elements as Character Strings     

Chapter 8: Text Operations     
Some Useful Text Functions     
Finding Things     
Regular Expressions     
Processing Raw Text Data     
Scraping the Web for Fun And Profit     

Chapter 9: Working With Date And Time DataDates in R     
Dates in R     
Formatting Dates for R     
Working with POSIX Dates     
Special Date Operations     
Formatting Dates for Output     
Time Series Data     
Creating Moving Averages in Time-Series Data     
Lagged Variables in Time-Series Data     
Differencing Variables in Time-Series Data     
The Limitations of ts Data     

Chapter 10: Data Merging And Aggregation     
Dataset Concatenation     
Match Merging     
Keyed Table Look-up Merging     
Aggregating Data     
Transposing and Rotating Datasets     

Chapter 11: Dealing with Missing Data     
Reading Data with Missing Values     
Summarizing Missing Values     
The Missing Values Functions     
Recoding Missing Values     
Missing Values And Regression Modeling     
Visualizing Missing Data     

Chapter 12: R Graphics I: The Built-in Plots     
Scatter Plots     
Pairs Plots     
Line Plots     
Box Plots     
Histograms, Density Plots, and Bar Charts     
Dot Charts     
Pie Charts     
Mosaic Plots     

Chapter 13: R Graphics II: The Boring Stuff     
The Graphics Device     
Graphics Parameters     
The Plot Layout     
Graphic Coordinates in R     
Overlaying Plots     
Multiple Plots     

Chapter 14: R Graphics III: The Fun Stuff--Text     
Adding Text     
Setting up a Font     
Titles and Subtitles     
Creating a Legend     
Simple Axes and Axis Labels     
Building More Complex Axes     
Ad-hoc Text     

Chapter 15: R Graphics IV: The Fun Stuff--Shapes     
Doing Colors     
Custom Points     
Adding Lines     
Incorporating Images into Plots     
A Final Word about Aesthetics     

Chapter 16 from Here to Where?

Customer Reviews

Handbook / Manual
By: Kurt Taylor Gaubatz(Author)
384 pages
Media reviews

"The guide is detailed enough that students could practice these operations outside the classroom until they mastered them, which means that more class time can be spent discussing the conceptual issues in statistics."
– Ole J. Forsberg, Oklahoma State University

"R's visualization tools and its powerful graphics capabilities [...] make this book a popular choice for many applications."
– Charlotte Tate, San Francisco State University

"A strength is the author's thorough approach to the code without being [...] dull. I very much appreciate that the author describes R code idiosyncrasies while keeping the text light."
– Yulan Liang, University of Maryland, Baltimore

"[This book] does an excellent job of guiding readers through pitfalls common to R's data handling idiosyncrasies – pitfalls usually learned after hours of frustration and lamentation. The conversational, and at times humorous, style makes for a readable, enjoyable, and relaxed examination of a powerful computation tool with a steep learning curve. Each chapter is compartmentalized enough to be read separately, but the author includes chapter references [...] to tie the guide together as a whole [...] The author covers the full spectrum, plus, thankfully, quite a bit of material not usually included in other R introductions [...] The author covers the material in depth with nicely done examples. I was also very happy to see that the author included a section on programming etiquette in R – very nice."
– A. Dean Monroe, Angelo State University

"I very much appreciate the development of a text primarily devoted to the students and practitioners who are first-time users of R [...] It is a very gentle and easy-to-read introduction to R for anyone who might have been afraid of learning programming language [...] It [is] very easy to read and follow [...] The flow of the topics is logical and natural for teaching any computational language. With a good sense of humor, the text is highly user-friendly."
– Professor David Han, University of Texas, San Antonio

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