Master the programming language of choice among statisticiansand data analysts worldwide Coming to grips with R can be tough, even for seasonedstatisticians and data analysts. Enter R For Dummies, the quick,easy way to master all the R you'll ever need. Requiring no priorprogramming experience and packed with practical examples, easy,step-by-step exercises, and sample code, this extremely accessibleguide is the ideal introduction to R for complete beginners. Italso covers many concepts that intermediate-level programmers willfind extremely useful. Master your R ABCs ? get up to speed in no time with thebasics, from installing and configuring R to writing simple scriptsand performing simultaneous calculations on many variables Put data in its place ? get to know your way around lists, dataframes, and other R data structures while learning to interact withother programs, such as Microsoft Excel Make data dance to your tune ? learn how to reshape andmanipulate data, merge data sets, split and combine data, performcalculations on vectors and arrays, and much more Visualize it ? learn to use R's powerful data visualizationfeatures to create beautiful and informative graphicalpresentations of your data Get statistical ? find out how to do simple statisticalanalysis, summarize your variables, and conduct classic statisticaltests, such as t-tests Expand and customize R ? get the lowdown on how to find,install, and make the most of add-on packages created by the globalR community for a wide variety of purposes Open the book and find: Help downloading, installing, and configuring R Tips for getting data in and out of R Ways to use data frames and lists to organize data How to manipulate and process data Advice on fitting regression models and ANOVA Helpful hints for working with graphics How to code in R * What R mailing lists and forums can do for you

Autorentext

Andrie de Vries is a market research consultant specializing in surveys, statistical analysis, and strategy.

Joris Meys is a statistician and R programmer with the faculty of bio-engineering at the University of Ghent.

Klappentext

Master the programming language of choice among statisticians and data analysts worldwide

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.

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
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
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
Visualize it learn to use R's powerful data visualization features to create beautiful and informative graphical presentations of your data
Get statistical find out how to do simple statistical analysis, summarize your variables, and conduct classic statistical tests, such as t-tests
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
Open the book and find:
Help downloading, installing, and configuring R
Tips for getting data in and out of R
Ways to use data frames and lists to organize data
How to manipulate and process data
Advice on fitting regression models and ANOVA
Helpful hints for working with graphics
How to code in R
What R mailing lists and forums can do for you
Learn to:
Use R for data analysis and processing
Write functions and scripts for repeatable analysis
Create high-quality charts and graphics
Perform statistical analysis and build models