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SAGE Research Methods SAGE Research Methods (Restricted to University of Ottawa)

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## Details

Genre/Form: | Electronic books |
---|---|

Additional Physical Format: | Print version |

Material Type: | Document, Internet resource |

Document Type: | Internet Resource, Computer File |

All Authors / Contributors: |
Kurt Taylor Gaubatz |

ISBN: | 9781483346878 1483346870 9781483372310 1483372316 9781483346885 1483346889 |

OCLC Number: | 931602024 |

Notes: | 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 Factors Coercing Storage Modes The Curse of Number-Character-Factor Confusion Conclusions 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 |

Description: | 1 online resource (460 pages) |

Contents: | Plots Box Plots Histograms, Density Plots, and Bar Charts Dot Charts Pie Charts Mosaic Plots Conclusions Chapter 13: R Graphics II: The Boring Stuff The Graphics Device Graphics Parameters The Plot Layout Graphic Coordinates in R Overlaying Plots Multiple Plots Conclusions 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 Shapes Incorporating Images into Plots A Final Word about Aesthetics Chapter 16 from Here to Where? |

Responsibility: | Kurt Taylor Gaubatz, Old Dominion University. |

### Abstract:

## Reviews

*Editorial reviews*

Publisher Synopsis

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

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