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Descriptions du produit

Discovering Statistics Using R The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences. Full description

Détails sur le produit

  • Broché: 992 pages
  • Editeur : SAGE Publications Ltd (22 mars 2012)
  • Langue : Anglais
  • ISBN-10: 1446200469
  • ISBN-13: 978-1446200469
  • Dimensions du produit: 3,8 x 19 x 25,4 cm
  • Moyenne des commentaires client : 5.0 étoiles sur 5  Voir tous les commentaires (2 commentaires client)
  • Classement des meilleures ventes d'Amazon: 2.090 en Livres anglais et étrangers (Voir les 100 premiers en Livres anglais et étrangers)
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1 internautes sur 1 ont trouvé ce commentaire utile  Par Miss Laura J Rennie le 25 février 2014
Format: Broché Achat vérifié
I have already read Andy Field's SPSS version of the book, so I bought this for the introduction to R, rather than statistics. It was easy enough to skip the beginning parts of each chapter explaining the theory behind the statistics and go straight to the parts showing how to carry out the analyses using R. Fantastic book, very very pleased with it. There is also an excellent, very clear introduction to multi-level modelling in Chapter 19.
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Par KRL le 14 janvier 2015
Format: Broché Achat vérifié
I highly recommend this book for beginners. Although the explanations are a little lengthy they are very clear and pertinent. This book is aimed at readers with a moderate proficiency in maths (for example matrix calculus is avoided). However, it explains the history, backgound and main insights behind statistics reasonning very well. As a result, from an intuitive viewpoint, this book would also be helpful background reading to more mathematically minded readers such as Engineering and Physics students. My hearty congratulations to the authors for having produced such a helpful and well thought out teaching book.
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Amazon.com: 52 commentaires
45 internautes sur 45 ont trouvé ce commentaire utile 
A great introduction to statistics and to R! 19 octobre 2012
Par andurion - Publié sur Amazon.com
Format: Relié
Being familiar with the author's SPSS book and wanting to learn R, I leapt at the chance to purchase this book. As I write this, I've been able to go through all the chapters save the last two. The book is a great overview of statistics concepts and provides a gentle, yet comprehensive, introduction to the R language. I'm extremely pleased I bought it.

The author's writing style is conversational and humorous, and some of his examples are outrageous (I didn't know whether to laugh or cry during the logistic regression chapter!). I think this would make the material more accessible to students who are ambivalent about statistics and R. However, though the material is presented in an easy-going manner, it is nevertheless quite comprehensive. The essence of each statistical method is discussed thoroughly, and the procedures for doing these tests in R are clearly detailed in a step by step manner.

What I liked most about the book were the problems at the end of each chapter and the detailed solutions to those problems on the book's accompanying website. I found these excellent for self-study.

To be clear, the book is not the most technical treatise on either statistics or R. The book gives a good overview of the concepts of each statistical method, but computation is kept to a minimum. Similarly, while the book describes how to create functions in R and has several challenging examples, you will only scratch the surface of what R can do. It seems intended primarily for non-mathematics undergraduate students who aspire to doing research in their fields. However, for someone like me who wanted a context in which to become familiar with R, it is invaluable.

The main problem I can see with the book was that there were some missing files for some of the end-of-chapter problems. I, personally, didn't think it was all that bad, as the same data was used in the author's SPSS book and I knew where to look for those SPSS files. Search for "field3e spss files" on your internest search engine of choice. However, that's not apparent to someone who doesn't know about the SPSS book, so I can see how it mars the final product somewhat. I'm still willing to give the book 5 stars, though!

In summary, this is a great book if you want a basic, yet very comprehensive, overview of statistics concepts and want to start your journey into R. Again, I'm very pleased I purchased it!
16 internautes sur 16 ont trouvé ce commentaire utile 
The Best Introduction to Statistics Available 20 avril 2013
Par nevergivenaname88 - Publié sur Amazon.com
Format: Broché Achat vérifié
Andy Field writes some of the most intuitive and entertaining accounts of statistics available, and this book is no exception to that standard. This book is geared towards those who want to start from the beginning and progress through a complete account of the most common methods in statistics based on the general linear model. If you are a beginner, this is one of the best places to start. If you are experienced, this book is a great reference to have around.

The most enjoyable aspect of this book, aside from its humor, is that Field addresses issues of using robust statical methods when assumptions are not met in the data. Instead of glossing over the issues, Field provides the most recent findings in the field and even examples of how to run robust tests in R. However, note if you want to do something very complicated with robust methods, this book is not a cure all, and you would be hard pressed to find one that is.

With regards to R, this book will get you up and running with R even if you have no previous experience with R or programming languages in general. However, a few of the R libraries have changed since this edition's publication, so you will need to search a bit to fix a few errors, but it's not hard and is good practice.

Finally, I must mention that Andy Field has gone out of his way to provide datasets and examples like no other author I have encountered. The book has a companion website full of these datasets and all of the R scripts used in the book. Additionally, the companion website is packed full of extra material for each chapter in the book. Finally, Field has several videos posted to the website which includes a lecture series on statistics.
19 internautes sur 21 ont trouvé ce commentaire utile 
Great Stats Book! 13 juillet 2012
Par ClinicalPsycStudent - Publié sur Amazon.com
Format: Broché
I loved the SPSS version of this book, and I was so excited to see the R version. Everyone who has attempted to learn R knows that there is a HUGE learning curve. Andy, Jeremy, and Zoë have found a way to make it so much easier with step-by-step code explanations and lots of humor. The companion site is great, too! Thank you for making stats enjoyable, and thank you for the laughs!
17 internautes sur 19 ont trouvé ce commentaire utile 
I recommend buy the hardcover 23 octobre 2014
Par Ísis da Costa Arantes - Publié sur Amazon.com
Format: Broché Achat vérifié
The book contents are very good, but the quality of the book is poor. I ordered one paperback and the pages were falling of the book in one month of use. I returned the book and the second book that I have received has the same problem. The page were falling of again. I'm very careful using the book, and it look like new. I believe it happened because of the poor quality.
I recommend buy the hard cover. I'm very frustrated about that. I have attached 2 pics (1st book and the 2nd book).
8 internautes sur 9 ont trouvé ce commentaire utile 
Very good for R - perhaps less good for statistics 2 mai 2014
Par L. Lipsey - Publié sur Amazon.com
Format: Broché Achat vérifié
I chose this book because I wanted to learn R through a progression of examples, and for that it has served well. I would recommend it for that purpose. My understanding of statistics, though, has not progressed as much as my R programming.

Specifically, I struggled in almost every chapter with "assumptions" - the criteria that must be met to justify the use of a particular statistical method. How important is each one? Why is it important? What exactly is it testing for, or trying to prevent you from doing?Close reading of the text was usually unhelpful to my understanding, and I frequently had to turn to outside sources. After a fair amount of struggle with the topic, here's what I've learned:

Basically, this issue is confusing because the whole idea of assumption checking is a simplification born out of the rise of statistics software. Which allows people like me, with limited mathematical literacy, to blithely run lots of analyses using wildly inappropriate and mis-specified models, then report the results as if they were something other than meaningless noise. If I actually understood how the models work, when they fail, and how to choose a meaningful specification, then I wouldn't need strict guidelines for assumption checking.

The problem is that the simplification is an oversimplification. A checklist of assumptions is no substitute for an understanding of the reasoning behind the modeling techniques. There will be cases where the model is appropriate even if you fail an item on the checklist, and cases where the model is inappropriate even if your data happens to check all the boxes. A checklist will never tell you that there's a better technique for your purposes. And it will always be hard to get a straight answer to questions like "how much is too much?" because the checklist thresholds are arbitrary in the first place, and therefore constantly open to debate.

Field is very little help in understanding how the models work or why they fail. Instead he takes a cookbook approach that mostly amounts to glorifying checklists. To the point that I suspect at least one of his chapters - on analysis of covariance - uses a mis-specified model as its core example (though it checks all the checklist boxes). It certainly doesn't look much like the appropriate situations for the technique according to outside sources, including some sources he cites in his bibliography.

I learned quite a bit of R. But if I want more than a surface understanding of statistics, I'm going to need another book.
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