R for Everyone: Advanced Analytics and Graphics et plus d'un million d'autres livres sont disponibles pour le Kindle d'Amazon. En savoir plus


ou
Identifiez-vous pour activer la commande 1-Click.
ou
en essayant gratuitement Amazon Premium pendant 30 jours. Votre inscription aura lieu lors du passage de la commande. En savoir plus.
Amazon Rachète votre article
Recevez un chèque-cadeau de EUR 9,41
Amazon Rachète cet article
Plus de choix
Vous l'avez déjà ? Vendez votre exemplaire ici
Désolé, cet article n'est pas disponible en
Image non disponible pour la
couleur :
Image non disponible

 
Commencez à lire R for Everyone: Advanced Analytics and Graphics sur votre Kindle en moins d'une minute.

Vous n'avez pas encore de Kindle ? Achetez-le ici ou téléchargez une application de lecture gratuite.

R for Everyone: Advanced Analytics and Graphics [Anglais] [Broché]

Jared P. Lander

Prix : EUR 20,37 LIVRAISON GRATUITE En savoir plus.
o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o
Il ne reste plus que 9 exemplaire(s) en stock (d'autres exemplaires sont en cours d'acheminement).
Expédié et vendu par Amazon. Emballage cadeau disponible.
Voulez-vous le faire livrer le vendredi 18 avril ? Choisissez la livraison en 1 jour ouvré sur votre bon de commande. En savoir plus.

Formats

Prix Amazon Neuf à partir de Occasion à partir de
Format Kindle EUR 15,13  
Broché EUR 20,37  

Description de l'ouvrage

19 décembre 2013

Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals


Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution.

Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks.

Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques.

By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most.

 

COVERAGE INCLUDES

• Exploring R, RStudio, and R packages

• Using R for math: variable types, vectors, calling functions, and more

• Exploiting data structures, including data.frames, matrices, and lists

• Creating attractive, intuitive statistical graphics

• Writing user-defined functions

• Controlling program flow with if, ifelse, and complex checks

• Improving program efficiency with group manipulations

• Combining and reshaping multiple datasets

• Manipulating strings using R’s facilities and regular expressions

• Creating normal, binomial, and Poisson probability distributions

• Programming basic statistics: mean, standard deviation, and t-tests

• Building linear, generalized linear, and nonlinear models

• Assessing the quality of models and variable selection

• Preventing overfitting, using the Elastic Net and Bayesian methods

• Analyzing univariate and multivariate time series data

• Grouping data via K-means and hierarchical clustering

• Preparing reports, slideshows, and web pages with knitr

• Building reusable R packages with devtools and Rcpp

• Getting involved with the R global community

 


Offres spéciales et liens associés


Les clients ayant consulté cet article ont également regardé


Descriptions du produit

Biographie de l'auteur

Jared P. Lander is the owner of Lander Analytics, a statistical consultanting firm based in New York City, the organizer of the New York Open Statistical Programming Meetup and an adjunct professor of statistics at Columbia University. He is also a tour guide for Scott’s Pizza Tours and an advisor to Brewla Bars, a gourmet ice pop startup. With an M.A. from Columbia University in statistics, and a B.A. from Muhlenberg College in mathematics, he has experience in both academic research and industry. His work for both large and small organizations spans politics, tech startups, fund raising, music, finance, healthcare and humanitarian relief efforts. He specializes in data management, multilevel models, machine learning, generalized linear models, visualization, data management and statistical computing

 


Détails sur le produit


En savoir plus sur l'auteur

Découvrez des livres, informez-vous sur les écrivains, lisez des blogs d'auteurs et bien plus encore.

Commentaires en ligne 

Il n'y a pas encore de commentaires clients sur Amazon.fr
5 étoiles
4 étoiles
3 étoiles
2 étoiles
1 étoiles
Commentaires client les plus utiles sur Amazon.com (beta)
Amazon.com: 4.7 étoiles sur 5  13 commentaires
29 internautes sur 31 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Really useful 25 janvier 2014
Par Dimitri Shvorob - Publié sur Amazon.com
Format:Format Kindle
To get the negatives out of the way: it's unfortunate that, having invested in appealing graphic design - the book looks just so much nicer than the spartan O'Reilly titles - Addison Wesley have not provided the author with similarly solid editorial support, resulting in a book that definitely feels rushed. There are typos, cosmetic blemishes (one regular annoyance is a table that's too wide for a page - one could fit it using a smaller font, but instead the table ends up split across twice as many rows), a couple of statistical blunders (on pp. 172 and 263), things that could have been left out, things that should have been included (oddly, the chapter on joins never mentions outer joins, and, in fact, does not explain what a join is) - and, finally, time and again, things that should have been explained better. I do not feel that "R for Everyone" is the best available introduction to R, and continue to endorse Robert Kabacoff's high-quality "R in Action" in that capacity.

Where "R for Everyone" differs from "R in Action" - and, coming to the positives, where it wins out - is in intermediate-R territory. One important example is coverage of "ggplot2". Whereas "R in Action" discusses the "old school" R graphics, "R for Everyone" goes with "ggplot2", becoming the second popular book (after Winston Chang's "R Graphics Cookbook") to discuss the package - and although its explanation of "ggplot2" syntax is sketchy, the samples found throughout the book do build into a useful "ggplot2" gallery that actually brought me over the fence. "plyr" package, an important data-manipulation aid, is another example, and another "R in Action" no-show. So is "data.table". So is "knitr", used to produce reports. So is "rcpp", used to interface R and C++. So is R package-building. (You will notice that the topics become more advanced. These are introductions rather than substantial explorations, but awareness is a valuable thing). In the book's second half, when discussion moves from R to statistics-with-R, the author continues to manage to find original material; statistical explanations may be brief - this is not a textbook - but examples, and pointers to useful R utilities, are much appreciated.

I own just one R book - literally, "The R Book", by Crawley - but "R for Everyone" will be joining it; this has got to be a compliment. Kudos to Jared Lander for writing an original, substantial, useful book.
21 internautes sur 25 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Current / Readable / Well-paced 4 janvier 2014
Par Edward E. Rigdon - Publié sur Amazon.com
Format:Broché|Achat authentifié par Amazon
I am still a novice in R, though I have used it for a while. I ordered this book because I need a more solid background in R for a major project. This book feels like exactly what I was looking for--like an experienced user sitting beside me helping me along. It is definitely *not* just a rehash of online pdf guides (which can be hard to parse). I am already marking pages that tell me things I never knew but needed to know. And the pacing of information "feels right"--no more than what I need to know, about when I need to know it. Just-released, its time references are as recent as September 2013, and that is important, because the R experience has evolved from something crude but full of possibilities to something much more rich, with an ecosystem of supporting tools. If you are like me, then I think you will really enjoy Jared lander's R for Everyone.
7 internautes sur 7 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 great to get you going in R 29 janvier 2014
Par Kathy W. Chiang - Publié sur Amazon.com
Format:Broché|Achat authentifié par Amazon
I have several R books that I have started but had to set aside because I got busy and the book got complicated. I am about 60% through this one and still going strong. It is written with just the right amount of detail to keep you learning and moving without getting bogged down. It's like one book sized tutorial, by following along with the book, you can get started actually doing things in R, with great code examples to come back to. After going through this book, I will be able to make much better use of my other R books.
6 internautes sur 6 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Very good introductory book for R 24 janvier 2014
Par Vedette Bianciotti - Publié sur Amazon.com
Format:Format Kindle
I consume tech books at a fast rate. I love to dip my toe in everything. Coming from a Ruby/Node background I have found the R language/environment something that takes getting used to and this book is a great example of how a learning book should approach something important but out of the ordinary (in terms of OOP languages).

Mixing learning data analytics and the language itself, I found myself being more able to pick up R. It is likely that my struggles with R come from a lack of background in traditional computer science or Maths and this helped bridge the gap as well as teach me R.

It might be that anyone with a serious background in Matlab or Octave might find this a little introductory but as a beginner it hit the spot. I haven't finished the book but I truly recommend this for anyone looking into moving into data science/statistical programming or the R language.
5 internautes sur 6 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Brilliant - Best book to get started with R 25 janvier 2014
Par J. DeSiena - Publié sur Amazon.com
Format:Broché
Great Book for Business people wanting to use R to analyze data and predict the future. Concepts are easy to grasp and are displayed in a manner that is easy to understand yet very informative. If you plan to use predictive analytics in your organization, this book is a must read for your entire staff.
Ces commentaires ont-ils été utiles ?   Dites-le-nous
ARRAY(0xab7d1564)

Discussions entre clients

Le forum concernant ce produit
Discussion Réponses Message le plus récent
Pas de discussions pour l'instant

Posez des questions, partagez votre opinion, gagnez en compréhension
Démarrer une nouvelle discussion
Thème:
Première publication:
Aller s'identifier
 

Rechercher parmi les discussions des clients
Rechercher dans toutes les discussions Amazon
   


Rechercher des articles similaires par rubrique


Commentaires

Souhaitez-vous compléter ou améliorer les informations sur ce produit ? Ou faire modifier les images?