The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: *The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops *Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R *How to access R’s thousands of functions, libraries, and data sets *How to draw valid and useful conclusions from your data *How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis.
Author: Tilman M. Davies
Publisher: No Starch Press
The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.
Becker R. A., Chambers J. M. and Wilks A. R. The New S Language: A
Programming Environment for Data Analysis and Graphics. Chapman & Hall ...
Braun J. W. and Murdoch D. J. A First Course in Statistical Programming with R.
Cambridge University Press, 1st edition, January 2008. 7. ... Crawley M. J. The R
Book. Wiley ...
Author: Pierre Lafaye de Micheaux
Publisher: Springer Science & Business
Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.
NUMERICAL COMPUTATION R.A. Thisted ... The purpose of this book is to
describe some of the more interesting and promising areas of statistical
computation, and to ... It is perhaps unfortunate that little of this exciting flavor
pervades the first course in statistical methods, or the first course in structured
Author: R.A. Thisted
With interest growing in areas of forestry, conservation and other natural sciences, the need to organize and tabulate large amounts of forestry and natural science information has become a necessary skill. Previous attempts of applying statistical methods to these areas tend to be over-specialized and of limited use; an elementary text using methods, examples and exercises that are relevant to forestry and the natural sciences is long overdue. This book utilizes basic descriptive statistics and probability, as well as commonly used statistical inferential tools to introduce topics that are commonplace in a forestry context such as hypothesis texting, design of experiments, sampling methods, nonparametric tests and statistical quality control. It also contains examples and exercises drawn from the fields of forestry, wood science, and conservation.
Many were instrumental in the development of this book, and we gratefully
acknowledge the contribution of these authors. ... A First Course. 7th Edition.
Prentice-Hall, Upper Saddle River, New Jersey. Huntsberger, D.V. and
Billingsley, P. 1973. ... Statistical. Software. Dilorio, F.C. 1991. SAS Applications
Programming: A Gentle Introduction. Duxbury Press, Boston ... Introductory
Probability and Statistics: Applications for 317 Forestry and Natural Sciences (A.
Kozak, R.A. Kozak, C.L. ...
A world list of books in the English language.
Category: American literature
Olshen, R. A., and Stone. C. J. (1984) ... Knuth, D. E. (1973), The Art of Computer
Programming, Reading, MA: Addison-Wesley. ... I would certainly recommend
this book for a first course on Markov chains and their applications at the
... statistical difficulties , 8 , 21 ; use of machinery , see Machinery ; with different
crops , 228 , 415 , 565 ; worked by hand , 239 , 282 ; see also Experiment ,
Experimental Field -note - book , 248 , 539 ; plan of experiment , 267 , 273-4 ,
279 , 284 ...
Author: Arthur Asquith Rayner
Category: Agricultural mathematics
The story of R. A. Fisher using this same test and finding Gregor J. Mendel's data
on peas too good a fit to the genetic theory he was propounding is a fascinating
... An Introduction to Statistical Methods & Data Analysis, 2nd ed. by Lyman 0tL
Wadsworth, Inc., Belmont, CA, 1984. ... This book presents all of the standard first
-course topics plus many additional techniques not found in textbooks aimed for
this audience. ... Coding formulas and grouped data formulas are also included.
Category: Quality control
All prices are net prices , SECTION NEWS Statistics and the Environment Second
Call for Nominations ... principles in this emerging field at a level that is
accessible to students and researchers with a first course in biostatistics . ... R for
SAS and R. A. Muenchen , University SPSS Users of Tennessee , Knoxville , TN ,
USA This book demonstrates which of the ... Content Introduction The five main
parts of SAS and SPSS Programming conventions Typographic conventions >
Author: American Statistical Association
First practical treatment of small-sample asymptotics, enabling practitioners to apply new methods with confidence.
Case Studies in Small-Sample Statistics A. R. Brazzale, A. C. Davison, N. Reid ...
Basic results about likelihood inference, which we call first order asymptotics,
were developed in fundamental work by R. A. Fisher during the 1920s, and now
form an essential and widely taught part of both elementary and advanced
courses in statistics. ... The purpose of this book is dispel this view, showing how
higher order asymptotics may be applied in realistic examples with very little
more effort ...
Author: A. R. Brazzale
Publisher: Cambridge University Press
Category: Business & Economics
(4th printing, 1976) 0-8053-2500-X 0-8053-2501-8 Paper Statistical Mechanics:
A Set of Lectures. 1972 ... 0-201-02028-9 level II: Teacher's Resource Book,
Book 00-201-02407-1 Teacher's Resource Book, Books 1 and 20-201-02135-8 [
eacher's Resource Book, ... 0-201-03571-5 'linn, R.A. Fundamentals of Metal
Casting. ... 0-8053-2560-3 0-8053-2561-1 Paper Foster, C.C. Programming a
Microcomputer: 6502. ... 0-201-02078-5 Foxley, E. & Neave, H.R. A First Course
in ALGOL 60.
Category: American literature
As in its first edition, the new edition of Quantitative Corpus Linguistics with R demonstrates how to process corpus-linguistic data with the open-source programming language and environment R. Geared in general towards linguists working with observational data, and particularly corpus linguists, it introduces R programming with emphasis on: data processing and manipulation in general; text processing with and without regular expressions of large bodies of textual and/or literary data, and; basic aspects of statistical analysis and visualization. This book is extremely hands-on and leads the reader through dozens of small applications as well as larger case studies. Along with an array of exercise boxes and separate answer keys, the text features a didactic sequential approach in case studies by way of subsections that zoom in to every programming problem. The companion website to the book contains all relevant R code (amounting to approximately 7,000 lines of heavily commented code), most of the data sets as well as pointers to others, and a dedicated Google newsgroup. This new edition is ideal for both researchers in corpus linguistics and instructors who want to promote hands-on approaches to data in corpus linguistics courses.
This book is extremely hands-on and leads the reader through dozens of small applications as well as larger case studies.
Author: Stefan Th. Gries
***Choice Outstanding Academic Title Award Winner*** The dynamic, student focused textbook provides step-by-step instruction in the use of R and of statistical language as a general research tool. It is ideal for anyone hoping to: Complete an introductory course in statistics Prepare for more advanced statistical courses Gain the transferable analytical skills needed to interpret research from across the social sciences Learn the technical skills needed to present data visually Acquire a basic competence in the use of R. The book provides readers with the conceptual foundation to use applied statistical methods in everyday research. Each statistical method is developed within the context of practical, real-world examples and is supported by carefully developed pedagogy and jargon-free definitions. Theory is introduced as an accessible and adaptable tool and is always contextualized within the pragmatic context of real research projects and definable research questions. Author Robert Stinerock has also created a wide range of online resources, including: R scripts, complete solutions for all exercises, data files for each chapter, video and screen casts, and interactive multiple-choice quizzes.
It is ideal for anyone hoping to: Complete an introductory course in statistics Prepare for more advanced statistical courses Gain the transferable analytical skills needed to interpret research from across the social sciences Learn the ...
Author: Robert Stinerock
The Burrows-Wheeler Transform is one of the best lossless compression me- ods available. It is an intriguing — even puzzling — approach to squeezing redundancy out of data, it has an interesting history, and it has applications well beyond its original purpose as a compression method. It is a relatively late addition to the compression canon, and hence our motivation to write this book, looking at the method in detail, bringing together the threads that led to its discovery and development, and speculating on what future ideas might grow out of it. The book is aimed at a wide audience, ranging from those interested in learning a little more than the short descriptions of the BWT given in st- dard texts, through to those whose research is building on what we know about compression and pattern matching. The ?rst few chapters are a careful description suitable for readers with an elementary computer science ba- ground (and these chapters have been used in undergraduate courses), but later chapters collect a wide range of detailed developments, some of which are built on advanced concepts from a range of computer science topics (for example, some of the advanced material has been used in a graduate c- puter science course in string algorithms). Some of the later explanations require some mathematical sophistication, but most should be accessible to those with a broad background in computer science.
This book will serve as a reference for seasoned professionals or researchers in the area, while remaining accessible for senior undergraduate students or first year graduate students embarking upon research in compression, pattern matching ...
Author: Donald Adjeroh
Publisher: Springer Science & Business Media
INTERNATIONAL WORKSHOPS (at IAREC'17) (This book inclueds English (main) and Turkish languages) International Workshop on Mechanical Engineering International Workshop on Mechatronics Engineering International Workshop on Energy Systems Engineering International Workshop on Automotive Engineering and Aerospace Engineering International Workshop on Material Engineering International Workshop on Manufacturing Engineering International Workshop on Physics Engineering International Workshop on Electrical and Electronics Engineering International Workshop on Computer Engineering and Software Engineering International Workshop on Chemical Engineering International Workshop on Textile Engineering International Workshop on Architecture International Workshop on Civil Engineering International Workshop on Geomatics Engineering International Workshop on Industrial Engineering International Workshop on Food Engineering International Workshop on Aquaculture Engineering International Workshop on Agriculture Engineering International Workshop on Mathematics Engineering International Workshop on Bioengineering Engineering International Workshop on Biomedical Engineering International Workshop on Genetic Engineering International Workshop on Environmental Engineering International Workshop on Other Engineering Science
INTERNATIONAL WORKSHOPS (at IAREC'17) (This book inclueds English (main) and Turkish languages) International Workshop on Mechanical Engineering International Workshop on Mechatronics Engineering International Workshop on Energy Systems ...
Author: Recep HALICIOGLU
Publisher: Dr. R. HALICIOGLU
Category: Technology & Engineering