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A Beginner s Guide to R

A Beginner s Guide to R Author Alain Zuur
ISBN-10 0387938370
Release 2009-06-24
Pages 220
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Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. This book contains everything you need to know to get started with R.

A Beginner s Guide to R

A Beginner s Guide to R Author Alain F. Zuur
ISBN-10 0387938362
Release 2009-07-01
Pages 218
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Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes.--[book cover]

Introductory R A Beginner s Guide to Data Visualisation Statistical Analysis and Programming in R

Introductory R  A Beginner s Guide to Data Visualisation  Statistical Analysis and Programming in R Author Robert Knell
ISBN-10 9780957597112
Release 2014-05-14
Pages 531
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R is now the most widely used statistical software in academic science and it is rapidly expanding into other fields such as finance. R is almost limitlessly flexible and powerful, hence its appeal, but can be very difficult for the novice user. There are no easy pull-down menus, error messages are often cryptic and simple tasks like importing your data or exporting a graph can be difficult and frustrating. Introductory R is written for the novice user who knows a little about statistics but who hasn't yet got to grips with the ways of R. This new edition is completely revised and greatly expanded with new chapters on the basics of descriptive statistics and statistical testing, considerably more information on statistics and six new chapters on programming in R. Topics covered include: A walkthrough of the basics of R's command line interface Data structures including vectors, matrices and data frames R functions and how to use them Expanding your analysis and plotting capacities with add-in R packages A set of simple rules to follow to make sure you import your data properly An introduction to the script editor and advice on workflow A detailed introduction to drawing publication-standard graphs in R How to understand the help files and how to deal with some of the most common errors that you might encounter. Basic descriptive statistics The theory behind statistical testing and how to interpret the output of statistical tests Thorough coverage of the basics of data analysis in R with chapters on using chi-squared tests, t-tests, correlation analysis, regression, ANOVA and general linear models What the assumptions behind the analyses mean and how to test them using diagnostic plots Explanations of the summary tables produced for statistical analyses such as regression and ANOVA Writing your own functions in R Using table operations to manipulate matrices and data frames Using conditional statements and loops in R programmes. Writing longer R programmes. The techniques of statistical analysis in R are illustrated by a series of chapters where experimental and survey data are analysed. There is a strong emphasis on using real data from real scientific research, with all the problems and uncertainty that implies, rather than well-behaved made-up data that give ideal and easy to analyse results.

R in Finance and Economics

R in Finance and Economics Author Abhay Kumar Singh
ISBN-10 9789813144484
Release 2016-12-14
Pages 264
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This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics. It is specifically targeted towards undergraduate and graduate students. It provides beginner-level introduction to R using RStudio and reproducible research examples. It will enable students to use R for data cleaning, data visualization and quantitative model building using statistical methods like linear regression, econometrics (GARCH etc), Copulas, etc. Moreover, the book demonstrates latest research methods with applications featuring linear regression, quantile regression, panel regression, econometrics, dependence modelling, etc. using a range of data sets and examples. Request Inspection Copy

Statistics with R

Statistics with R Author Robert Stinerock
ISBN-10 9781526421470
Release 2018-01-08
Pages 392
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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.

The R Book

The R Book Author Michael J. Crawley
ISBN-10 9781118448960
Release 2012-11-07
Pages 1080
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Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)

A Beginner s Guide to Data Exploration and Visualisation with R

A Beginner s Guide to Data Exploration and Visualisation with R Author Elena N. Ieno
ISBN-10 OCLC:907238435
Release 2015
Pages 161
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A Beginner s Guide to Data Exploration and Visualisation with R has been writing in one form or another for most of life. You can find so many inspiration from A Beginner s Guide to Data Exploration and Visualisation with R also informative, and entertaining. Click DOWNLOAD or Read Online button to get full A Beginner s Guide to Data Exploration and Visualisation with R book for free.

A Beginner s Guide to GLM and GLMM with R

A Beginner s Guide to GLM and GLMM with R Author Alain F. Zuur
ISBN-10 0957174136
Release 2013
Pages 256
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This book presents Generalized Linear Models (GLM) and Generalized Linear Mixed Models (GLMM) based on both frequency-based and Bayesian concepts.

A Beginner s Guide to Generalized Additive Models with R

A Beginner s Guide to Generalized Additive Models with R Author Alain F. Zuur
ISBN-10 0957174128
Release 2012
Pages 188
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A Beginner's Guide to Generalized Additive Models with R is exclusively available from:

Statistical Analysis with R

Statistical Analysis with R Author John M. Quick
ISBN-10 9781849512091
Release 2010-10-26
Pages 300
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Take control of your data and produce superior statistical analysis with R.


R Author Felix Alvaro
ISBN-10 1533685010
Release 2016-05-01
Pages 156
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Learn R Programming Today With This Easy, Step-By-Step Guide! Do you want to learn R Programming? Do you get overwhelmed by complicated lingo and want a guide that is easy to follow, detailed and written to make the process enjoyable? If so, "R: Easy R Programming for Beginners - Your Step-By-Step Guide To Learning R Programming" by Felix Alvaro is THE book for you! It covers the most essential topics you must learn to begin programming with R.With more than two million global users, the R language is rapidly turning into a top programming language specifically in the space of data science as well as statistics. What you are going to learn in this step-by-step beginner's guide is how to master the fundamentals of such a gorgeous open-source programming language which includes vectors, data frames and lists.Not only is the language growing in popularity, but the demand for R Programmers is also rising, with skilled programmers getting paid an average annual salary of $115,000 per year! What Separates This Book From The Rest? What separates this book from all the others out there is the approach to teaching. A lot of the books you will stumble upon simply throw information at you, leaving you confused and stuck.We believe that books of this nature should be easy to grasp and written in jargon-free English you can understand, making you feel confident and allowing you to grasp each topic with ease.To help you achieve this, the guide has been crafted in a step-by-step manner which we feel is the best way for you to learn a new subject, one step at a time. It also includes various images to give you assurance you are going in the right direction, as well as having exercises where you can proudly practice your newly attained skills. You Will Learn The Following: The history of R programming and its benefits How to install R & R Studio and work with code editors The fundamentals of R syntax Function & Arguments R Programming with user packages Organizing data in Vectors Working with Data-Frames and Matrices Creating Lists Effective coding in R Controlling Logical Flow Woking with base graphics Creating Facetted graphics using Lattice And much more! So don't delay it any longer. Take this opportunity and invest in this guide now. You will be amazed by the skills you will quickly attain! Buy This Guide Now! See you inside!

R Statistical Application Development by Example Beginner s Guide

R Statistical Application Development by Example Beginner s Guide Author Prabhanjan Narayanachar Tattar
ISBN-10 9781849519458
Release 2013-01-01
Pages 344
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Full of screenshots and examples, this Beginner's Guide by Example will teach you practically everything you need to know about R statistical application development from scratch. You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject.

R For Dummies

R For Dummies Author Andrie de Vries
ISBN-10 9781119055839
Release 2015-06-18
Pages 432
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Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more. R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2nd Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide. Covers downloading, installing, and configuring R Includes tips for getting data in and out of R Offers advice on fitting regression models and ANOVA Provides helpful hints for working with graphics R For Dummies, 2nd Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.

R by Example

R by Example Author Jim Albert
ISBN-10 9781461413653
Release 2012-01-28
Pages 359
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R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, this book is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data and this book is intended to be a useful resource for learning how to implement these procedures in R.

An Introduction to R for Spatial Analysis and Mapping

An Introduction to R for Spatial Analysis and Mapping Author Chris Brunsdon
ISBN-10 9781473911192
Release 2015-01-22
Pages 360
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"In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using 'out of the box' software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical 'how to' guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive 'how to' that takes students - of any discipline - from coding to actual applications and uses of R.

The Book of R

The Book of R Author Tilman M. Davies
ISBN-10 9781593277796
Release 2016-07-16
Pages 832
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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 Brain

The Brain Author Ammar Al-Chalabi
ISBN-10 9781780740539
Release 2008-02-01
Pages 272
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It has been remarked that if the brain were so simple we could understand it, we would be so simple we couldn’t. Commencing with a brief history of neuroscience, from the ancient practice of drilling holes in the head to relieve headaches to the latest results from MRI and CT scans, this accessible guide sets out to explore exactly what we do know about the brain. Including the most up-to-date research on the cerebral processes behind a wide array of human activity – from our capacity for language to how we remember – this lively and entertaining introduction assumes no previous scientific knowledge and offers a tantalizing glimpse into man’s most complex organ. Ammar Al-Chalabi is Honourary Consultant Neurologist at King’s College Hospital, and a Senior Lecturer at the Institute of Psychiatry, London. R. Shane Delamont is a Consultant Neurologist at King’s College Hospital, and Martin Turner is Wellcome Fellow in Neurology at The Institute of Psychiatry. All three have extensive experience of teaching the key principles of neuroscience, and between them their specialist fields of expertise cover all of the main areas of contemporary brain research.