r for excel users an introduction to r for excel analysts

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R For Excel Users

Author : John L. Taveras
ISBN : 1500566357
Genre :
File Size : 56. 4 MB
Format : PDF, Kindle
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R has a steep learning curve and, if taken in all at once, it can be overwhelming. But we can tame this curve by putting aside visualizations and analysis, and focusing on working with data. This book is all about data manipulation: importing, creating, modifying, filtering, summarizing and reshaping data sets. You will also go deep on the building blocks of R: vectors and functions. The language is simplified and technical lingo is kept to a minimum. You will see analogies to Excel where applicable, to ease your understanding of concepts. Supplemental articles and videos can be found at rforexcelusers.com

R For Microsoft Excel Users

Author : Conrad Carlberg
ISBN : 9780134571898
Genre : Business & Economics
File Size : 59. 26 MB
Format : PDF, Mobi
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This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Microsoft Excel can perform many statistical analyses, but thousands of business users and analysts are now reaching its limits. R, in contrast, can perform virtually any imaginable analysis–if you can get over its learning curve. In R for Microsoft® Excel Users, Conrad Carlberg shows exactly how to get the most from both programs. Drawing on his immense experience helping organizations apply statistical methods, Carlberg reviews how to perform key tasks in Excel, and then guides you through reaching the same outcome in R–including which packages to install and how to access them. Carlberg offers expert advice on when and how to use Excel, when and how to use R instead, and the strengths and weaknesses of each tool. Writing in clear, understandable English, Carlberg combines essential statistical theory with hands-on examples reflecting real-world challenges. By the time you’ve finished, you’ll be comfortable using R to solve a wide spectrum of problems–including many you just couldn’t handle with Excel. • Smoothly transition to R and its radically different user interface • Leverage the R community’s immense library of packages • Efficiently move data between Excel and R • Use R’s DescTools for descriptive statistics, including bivariate analyses • Perform regression analysis and statistical inference in R and Excel • Analyze variance and covariance, including single-factor and factorial ANOVA • Use R’s mlogit package and glm function for Solver-style logistic regression • Analyze time series and principal components with R and Excel

R Through Excel

Author : Richard M. Heiberger
ISBN : 9781441900524
Genre : Computers
File Size : 23. 72 MB
Format : PDF
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In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel seamlessly integrates the entire set of R's statistical and graphical methods into Excel, allowing students to focus on statistical methods and concepts and minimizing the distraction of learning a new programming language.

The R Book

Author : Michael J. Crawley
ISBN : 9781118448960
Genre : Mathematics
File Size : 54. 8 MB
Format : PDF, ePub, Docs
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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)

Introductory R A Beginner S Guide To Data Visualisation Statistical Analysis And Programming In R

Author : Robert Knell
ISBN : 9780957597112
Genre :
File Size : 50. 35 MB
Format : PDF, ePub
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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.

The Book Of R

Author : Tilman M. Davies
ISBN : 9781593277796
Genre : Computers
File Size : 43. 10 MB
Format : PDF, Docs
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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.

A First Course In Statistical Programming With R

Author : W. John Braun
ISBN : 9781107576469
Genre : Computers
File Size : 30. 78 MB
Format : PDF, Mobi
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Learn to program in R from the experts with this new, color edition of Braun and Murdoch's bestselling textbook.

Statistics For Ecologists Using R And Excel

Author : Mark Gardener
ISBN : 9781784271411
Genre : Science
File Size : 28. 46 MB
Format : PDF, ePub, Docs
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This is a book about the scientific process and how you apply it to data in ecology. You will learn how to plan for data collection, how to assemble data, how to analyze data and finally how to present the results. The book uses Microsoft Excel and the powerful Open Source R program to carry out data handling as well as producing graphs. Statistical approaches covered include: data exploration; tests for difference – t-test and U-test; correlation – Spearman’s rank test and Pearson product-moment; association including Chi-squared tests and goodness of fit; multivariate testing using analysis of variance (ANOVA) and Kruskal–Wallis test; and multiple regression. Key skills taught in this book include: how to plan ecological projects; how to record and assemble your data; how to use R and Excel for data analysis and graphs; how to carry out a wide range of statistical analyses including analysis of variance and regression; how to create professional looking graphs; and how to present your results. New in this edition: a completely revised chapter on graphics including graph types and their uses, Excel Chart Tools, R graphics commands and producing different chart types in Excel and in R; an expanded range of support material online, including; example data, exercises and additional notes & explanations; a new chapter on basic community statistics, biodiversity and similarity; chapter summaries and end-of-chapter exercises. Praise for the first edition: This book is a superb way in for all those looking at how to design investigations and collect data to support their findings. – Sue Townsend, Biodiversity Learning Manager, Field Studies Council [M]akes it easy for the reader to synthesise R and Excel and there is extra help and sample data available on the free companion webpage if needed. I recommended this text to the university library as well as to colleagues at my student workshops on R. Although I initially bought this book when I wanted to discover R I actually also learned new techniques for data manipulation and management in Excel – Mark Edwards, EcoBlogging A must for anyone getting to grips with data analysis using R and excel. – Amazon 5-star review It has been very easy to follow and will be perfect for anyone. – Amazon 5-star review A solid introduction to working with Excel and R. The writing is clear and informative, the book provides plenty of examples and figures so that each string of code in R or step in Excel is understood by the reader. – Goodreads, 4-star review

A Course In Statistics With R

Author : Prabhanjan N. Tattar
ISBN : 9781119152750
Genre : Computers
File Size : 68. 56 MB
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Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models. Key features: Integrates R basics with statistical concepts Provides graphical presentations inclusive of mathematical expressions Aids understanding of limit theorems of probability with and without the simulation approach Presents detailed algorithmic development of statistical models from scratch Includes practical applications with over 50 data sets

R For Dummies

Author : Andrie de Vries
ISBN : 9781119055839
Genre : Computers
File Size : 43. 71 MB
Format : PDF, Kindle
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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.

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