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! Read ! Introductory Statistics with R (Statistics and Computing) by Peter Dalgaard á eBook or Kindle ePUB. Introductory Statistics with R (Statistics and Computing) Excellent resource David B. Thompson I bought this book a little over a year ago when a friend and colleague insisted I learn the R system for our collaborative work. I am not a professional statistician, but an engineer and researcher who needs and uses statistics in the course of my professional work.I found this book approachable and informative from the non-professional perspective. (That is, from the viewpoint of a non-statistician.) I found enough examples to guide me through the process o
| Title | : | Introductory Statistics with R (Statistics and Computing) |
| Author | : | |
| Rating | : | 4.92 (849 Votes) |
| Asin | : | 0387954759 |
| Format Type | : | paperback |
| Number of Pages | : | 267 Pages |
| Publish Date | : | 2014-03-29 |
| Language | : | English |
Excellent resource David B. Thompson I bought this book a little over a year ago when a friend and colleague insisted I learn the R system for our collaborative work. I am not a professional statistician, but an engineer and researcher who needs and uses statistics in the course of my professional work.I found this book approachable and informative from the non-professional perspective. (That is, from the viewpoint of a non-statistician.) I found enough examples to guide me through the process of bringing my datasets into the R e. Very readable introduction This book provides a very readable introduction to basic statistical analysis using R (with occational references to S-Plus). The table of contents displays the topics and I thought they were generally well covered in enough detail to compute the statistics (but this is not a statistics text). Especially helpful are the additional analysis steps, such as graphing results, and the peripheral R issues. Small things I would change: expanded coverage of manipulating data (e.g., SPSS's RECODE, TEMP. "Twofold win: great introduction to useful statistics and R programming" according to Isaac S. Kohane. Despite the web, there are learning curves sufficiently steep that a well-organized book is the most effective introduction. However, too many of these introductions, particularly in programming and/or statistics are written with low content and high redundancy or with impenetrably high-density content. So, it is a rare sign of pedagogical mastery combined with the genuine confidence of the experienced practioner when an introductory book manages to achieve a balance that is just right.As I be
Peter Dalgaard has been a key member of the R Core Team since August 1997 and is well known among R users for his activity on. Peter Dalgaard is associate professor at the Biostatistical Department at the University of Copenhagen and has extensive experience in teaching within the PhD curriculum at the Faculty of Health Sciences. He was chairman of the Danish Society for Theoretical Statistics from 1996 to 2000
For experienced statisticians and data analysts, the book provides a good overview of the basic statistical analysis capabilities of R … prepares readers for later migration to S. … The present book is … a very useful guide for introducing a number of basic concepts and techniques necessary to practical statistics, covering both elementary statistics and actual programming in the R language. A supplementary R package can be downloaded and contains the data sets." (Zentralblatt für Didaktik der Mathematik, August, 2004)"This is a nice book on statistical methods and statistical computing in R, a
R is an Open Source implementation of the S language. A supplementary R package can be downloaded and contains the data sets.The statistical methodology includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one- and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. Exercises have been revised and answers are now provided in an Appendix.. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. The introductory chapter has been extended and reorganized as two chapters. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development.This book provides an elementary-level introduction to R, targeting both non-statistician
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