Read R For Excel Users: Introduction To R For Excel Analysts Books PDF

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by John L. Taveras

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by John L. Taveras

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

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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Conrad Carlberg

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Conrad Carlberg

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

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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Richard M. Heiberger, Erich Neuwirth

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Richard M. Heiberger, Erich Neuwirth

R, a free and open source program, is one of the most powerful and the fastest-growing statistics program. Microsoft Excel is the most widely used spreadsheet program, but many statisticians consider its statistical tools too limited.

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.

Data can be transferred between R and Excel “the Excel way” by selecting worksheet ranges and using Excel menus. R’s basic statistical functions and selected advanced methods are available from an Excel menu. Results of the computations and statistical graphics can be returned back into Excel worksheet ranges. RExcel allows the use of Excel scroll bars and check boxes to create and animate R graphics as an interactive analysis tool.

The book is designed as a computational supplement to introductory statistics texts and the authors provide RExcel examples covering the topics of the introductory course.

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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Michael J. Crawley

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Michael J. Crawley

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) 

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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Mark Gardener

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Mark Gardener

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, EcoBloggingA must for anyone getting to grips with data analysis using R and excel. – Amazon 5-star reviewIt has been very easy to follow and will be perfect for anyone. – Amazon 5-star reviewA 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

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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Andrie de Vries, Joris Meys

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Andrie de Vries, Joris Meys 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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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by W. John Braun, Duncan J. Murdoch

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by W. John Braun, Duncan J. Murdoch This new color edition of Braun and Murdoch’s bestselling textbook integrates use of the RStudio platform and adds discussion of newer graphics systems, extensive exploration of Markov chain Monte Carlo, expert advice on common error messages, motivating applications of matrix decompositions, and numerous new examples and exercises. This is the only introduction needed to start programming in R, the computing standard for analyzing data. Co-written by an R core team member and an established R author, this book comes with real R code that complies with the standards of the language. Unlike other introductory books on the R system, this book emphasizes programming, including the principles that apply to most computing languages, and techniques used to develop more complex projects. Solutions, datasets, and any errata are available from the book’s website. The many examples, all from real applications, make it particularly useful for anyone working in practical data analysis.

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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Tilman M. Davies

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Tilman M. Davies 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.

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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Robert J. Knell

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Robert J. Knell 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.

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Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Robert A. Muenchen

Read R For Excel Users: Introduction To R For Excel Analysts Books PDF by Robert A. Muenchen

R is a powerful and free software system for data analysis and graphics, with over 5,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R’s built-in functions. It steps through over 30 programs written in all three packages, comparing and contrasting the packages’ differing approaches. The programs and practice datasets are available for download.

The glossary defines over 50 R terms using SAS/SPSS jargon and again using R jargon. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. When finished, you will be able to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses.

This new edition has updated programming, an expanded index, and even more statistical methods covered in over 25 new sections.

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R for Excel Users
Language: en
Pages: 212

R for Excel Users

Authors: John L. Taveras
Categories:
Type: BOOK - Published: 2016-08-08 - Publisher: Createspace Independent Publishing Platform
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
The R Book
Language: en
Pages: 1080

The R Book

Authors: Michael J. Crawley
Categories: Mathematics
Type: BOOK - Published: 2012-11-07 - Publisher: John Wiley & Sons
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
R For Dummies
Language: en
Pages: 432

R For Dummies

Authors: Andrie de Vries, Joris Meys
Categories: Computers
Type: BOOK - Published: 2015-06-18 - Publisher: John Wiley & Sons
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,
R for Microsoft® Excel Users
Language: en
Pages: 272

R for Microsoft® Excel Users

Authors: Conrad Carlberg
Categories: Business & Economics
Type: BOOK - Published: 2016-11-11 - Publisher: Que Publishing
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,
R Through Excel
Language: en
Pages: 344

R Through Excel

Authors: Richard M. Heiberger, Erich Neuwirth
Categories: Computers
Type: BOOK - Published: 2010-01-23 - Publisher: Springer Science & Business Media
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