An essential library of basic commands you can copy and paste into R The powerful and open-source statistical programming language R is rapidly growing in popularity, but it requires that you type in commands at the keyboard rather than use a mouse, so you have to learn the language of R. But there is a shortcut, and that's where this unique book comes in. A companion book to Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, this practical reference is a library of basic R commands that you can copy and paste into R to perform many types of statistical analyses. Whether you're in technology, science, medicine, business, or engineering, you can quickly turn to your topic in this handy book and find the commands you need. Comprehensive command reference for the R programming language and a companion book to Visualize This: The FlowingData Guide to Design, Visualization, and Statistics Combines elements of a dictionary, glossary, and thesaurus for the R language Provides easy accessibility to the commands you need, by topic, which you can cut and paste into R as needed Covers getting, saving, examining, and manipulating data; statistical test and math; and all the things you can do with graphs Also includes a collection of utilities that you'll find useful Simplify the complex statistical R programming language with The Essential R Reference. .
Introduction xv Theme 1: Data 1 Data Types 3 Types of Data 3 Altering Data Types 16 Testing Data Types 18 Creating Data 22 Creating Data from the Keyboard 22 Creating Data from the Clipboard 29 Adding to Existing Data 29 Importing Data 39 Importing Data from Text Files 39 Importing Data from Data Files 46 Saving Data 49 Saving Data as a Text File to Disk 50 Saving Data as a Data File to Disk 59 Viewing Data 61 Listing Data 61 Data Object Properties 74 Selecting and Sampling Data 107 Sorting and Rearranging Data 117 Summarizing Data 121 Summary Statistics 121 Summary Tables 136 Distribution of Data 146 Density Functions 148 Probability Functions 152 Quantile Functions 158 Random Numbers 161 Theme 2: Math and Statistics 167 Mathematical Operations 169 Math 169 Logic 188 Complex Numbers .194 Trigonometry 202 Hyperbolic Functions 206 Matrix Math 206 Summary Statistics 223 Simple Summary Stats 223 Tests of Distribution 235 Differences Tests 240 Parametric Tests 241 Non-parametric 252 Correlations and Associations 267 Correlation 267 Association and Goodness of Fit 275 Analysis of Variance and Linear Modeling 283 ANOVA 284 Linear Modeling 300 Miscellaneous Methods 317 Clustering 318 Ordination 324 Time Series 331 Non-linear Modeling and Optimization 333 Theme 3: Graphics 347 Making Graphs 348 Types of Graphs 349 Saving Graphs 389 Adding to Graphs 398 Adding Data 398 Adding Lines 404 Adding Shapes 416 Adding Text 422 Adding Legends 432 Graphical Parameters 436 Using the par Command 437 Altering Color 439 Altering Axis Parameters 446 Altering Text Parameters 453 Altering Line (and Box) Parameters 456 Altering Plot Margins 459 Altering the Graph Window 462 Theme 4: Utilities 475 Install 476 Installing R 477 Installing Packages 477 Using R 480 Using the Program 480 Additional Packages 486 Programming 490 Managing Functions 491 Saving and Running Scripts 498 Conditional Control 502 Returning Results 507 Error Trapping 525 Constants 527 Index 529
Dr. Mark Gardener is an ecologist, lecturer, and writer who discovered R while doing data analysis for his doctorate in ecology and evolutionary biology. He conducts courses in R, ecology, and data analysis for a variety of organizations. Mark is also the author of Beginning R: The Statistical Programming Language, a Wrox book published by Wiley.
Here's the ultimate dictionary, glossary,and thesaurus for the R language The cross-platform, open source language R provides powerful tools for data analysis and reporting, but its complexities can be a bit daunting. To use the built-in help system, you must know the command names — the vocabulary and grammar of R. This book contains more than 400 command names arranged by topic, with plenty of examples, related commands, and cross-references. It's the quintessential resource for R beginners and veterans alike. You will find: Commands grouped by theme, letting you search for one based on the task you wish to accomplish Explanations showing what each command does Commonly used parameters for each command Examples and related commands Cross-references for command names with multiple applications Example datasets on the companion website
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