Details

R For Dummies


R For Dummies


2. Aufl.

von: Andrie de Vries, Joris Meys

19,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 04.06.2012
ISBN/EAN: 9781119963127
Sprache: englisch
Anzahl Seiten: 408

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

<p><b>Master the programming language of choice among statisticians and data analysts worldwide</b></p> <p>Coming to grips with R can be tough, even for seasoned statisticians and data analysts. Enter R For Dummies, the quick, easy way to master all the R you'll ever need. Requiring no prior programming experience and packed with practical examples, easy, step-by-step exercises, and sample code, this extremely accessible guide is the ideal introduction to R for complete beginners. It also covers many concepts that intermediate-level programmers will find extremely useful.</p> <ul> <li>Master your R ABCs ? get up to speed in no time with the basics, from installing and configuring R to writing simple scripts and performing simultaneous calculations on many variables</li> <li>Put data in its place ? get to know your way around lists, data frames, and other R data structures while learning to interact with other programs, such as Microsoft Excel</li> <li>Make data dance to your tune ? learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and much more</li> <li>Visualize it ? learn to use R's powerful data visualization features to create beautiful and informative graphical presentations of your data</li> <li>Get statistical ? find out how to do simple statistical analysis, summarize your variables, and conduct classic statistical tests, such as t-tests</li> <li>Expand and customize R ? get the lowdown on how to find, install, and make the most of add-on packages created by the global R community for a wide variety of purposes</li> <li>Open the book and find:</li> <li>Help downloading, installing, and configuring R</li> <li>Tips for getting data in and out of R</li> <li>Ways to use data frames and lists to organize data</li> <li>How to manipulate and process data</li> <li>Advice on fitting regression models and ANOVA</li> <li>Helpful hints for working with graphics</li> <li>How to code in R</li> <li>What R mailing lists and forums can do for you <br /> <br /> </li> </ul>
<p><b>Introduction 1</b></p> <p><b>Part I: R You Ready? 7</b></p> <p>Chapter 1: Introducing R: The Big Picture 9</p> <p>Chapter 2: Exploring R 15</p> <p>Chapter 3: The Fundamentals of R 31</p> <p><b>Part II: Getting Down to Work in R 43</b></p> <p>Chapter 4: Getting Started with Arithmetic 45</p> <p>Chapter 5: Getting Started with Reading and Writing 71</p> <p>Chapter 6: Going on a Date with R 93</p> <p>Chapter 7: Working in More Dimensions 103</p> <p><b>Part III: Coding in R 137</b></p> <p>Chapter 8: Putting the Fun in Functions 139</p> <p>Chapter 9: Controlling the Logical Flow 159</p> <p>Chapter 10: Debugging Your Code 179</p> <p>Chapter 11: Getting Help 193</p> <p><b>Part IV: Making the Data Talk 203</b></p> <p>Chapter 12: Getting Data into and out of R 205</p> <p>Chapter 13: Manipulating and Processing Data 219</p> <p>Chapter 14: Summarizing Data 253</p> <p>Chapter 15: Testing Differences and Relations 275</p> <p><b>Part V: Working with Graphics 299</b></p> <p>Chapter 16: Using Base Graphics 301</p> <p>Chapter 17: Creating Faceted Graphics with Lattice 317</p> <p>Chapter 18: Looking At ggplot2 Graphics 333</p> <p><b>Part VI: The Part of Tens 347</b></p> <p>Chapter 19: Ten Things You Can Do in R That You Would've Done in Microsoft Excel 349</p> <p>Chapter 20: Ten Tips on Working with Packages 359</p> <p><b>Appendix: Installing R and RStudio 365</b></p> <p><b>Index 371</b></p>
<p><b>Andrie de Vries</b> is a market research consultant specializing in surveys, statistical analysis, and strategy.</p> <p><b>Joris Meys</b> is a statistician and R programmer with the faculty of bio-engineering at the University of Ghent.</p>
<p><b>Master the programming language of choice among statisticians and data analysts worldwide</b></p> <p>Coming to grips with R can be tough, even for seasoned statisticians and data analysts. Enter <i>R For Dummies,</i> the quick, easy way to master all the R you'll ever need. Requiring no prior programming experience and packed with practical examples, easy, step-by-step exercises, and sample code, this extremely accessible guide is the ideal introduction to R for complete beginners. It also covers many concepts that intermediate-level programmers will find extremely useful.</p> <ul> <li>Master your R ABCs — get up to speed in no time with the basics, from installing and configuring R to writing simple scripts and performing simultaneous calculations on many variables</li> <li>Put data in its place — get to know your way around lists, data frames, and other R data structures while learning to interact with other programs, such as Microsoft Excel</li> <li>Make data dance to your tune — learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and much more</li> <li>Visualize it — learn to use R's powerful data visualization features to create beautiful and informative graphical presentations of your data</li> <li>Get statistical — find out how to do simple statistical analysis, summarize your variables, and conduct classic statistical tests, such as t-tests</li> <li>Expand and customize R — get the lowdown on how to find, install, and make the most of add-on packages created by the global R community for a wide variety of purposes</li> </ul> <p><b>Open the book and find:</b></p> <ul> <li>Help downloading, installing, and configuring R</li> <li>Tips for getting data in and out of R</li> <li>Ways to use data frames and lists to organize data</li> <li>How to manipulate and process data</li> <li>Advice on fitting regression models and ANOVA</li> <li>Helpful hints for working with graphics</li> <li>How to code in R</li> <li>What R mailing lists and forums can do for you</li> </ul> <p><b>Learn to:</b></p> <ul> <li>Use R for data analysis and processing</li> <li>Write functions and scripts for repeatable analysis</li> <li>Create high-quality charts and graphics</li> <li>Perform statistical analysis and build models</li> </ul>

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