Beyond Spreadsheets with R


Book Description

Summary Beyond Spreadsheets with R shows you how to take raw data and transform it for use in computations, tables, graphs, and more. You'll build on simple programming techniques like loops and conditionals to create your own custom functions. You'll come away with a toolkit of strategies for analyzing and visualizing data of all sorts using R and RStudio. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Spreadsheets are powerful tools for many tasks, but if you need to interpret, interrogate, and present data, they can feel like the wrong tools for the task. That's when R programming is the way to go. The R programming language provides a comfortable environment to properly handle all types of data. And within the open source RStudio development suite, you have at your fingertips easy-to-use ways to simplify complex manipulations and create reproducible processes for analysis and reporting. About the Book With Beyond Spreadsheets with R you'll learn how to go from raw data to meaningful insights using R and RStudio. Each carefully crafted chapter covers a unique way to wrangle data, from understanding individual values to interacting with complex collections of data, including data you scrape from the web. You'll build on simple programming techniques like loops and conditionals to create your own custom functions. You'll come away with a toolkit of strategies for analyzing and visualizing data of all sorts. What's inside How to start programming with R and RStudio Understanding and implementing important R structures and operators Installing and working with R packages Tidying, refining, and plotting your data About the Reader If you're comfortable writing formulas in Excel, you're ready for this book. About the Author Dr Jonathan Carroll is a data science consultant providing R programming services. He holds a PhD in theoretical physics. Table of Contents Introducing data and the R language Getting to know R data types Making new data values Understanding the tools you'll use: Functions Combining data values Selecting data values Doing things with lots of data Doing things conditionally: Control structures Visualizing data: Plotting Doing more with your data with extensions




R for Data Science


Book Description

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results




The R Book


Book Description

The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.




R Through Excel


Book Description

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 Book of R


Book Description

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.




Practical Data Science with R, Second Edition


Book Description

Summary Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You’ll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. About the technology Evidence-based decisions are crucial to success. Applying the right data analysis techniques to your carefully curated business data helps you make accurate predictions, identify trends, and spot trouble in advance. The R data analysis platform provides the tools you need to tackle day-to-day data analysis and machine learning tasks efficiently and effectively. About the book Practical Data Science with R, Second Edition is a task-based tutorial that leads readers through dozens of useful, data analysis practices using the R language. By concentrating on the most important tasks you’ll face on the job, this friendly guide is comfortable both for business analysts and data scientists. Because data is only useful if it can be understood, you’ll also find fantastic tips for organizing and presenting data in tables, as well as snappy visualizations. What's inside Statistical analysis for business pros Effective data presentation The most useful R tools Interpreting complicated predictive models About the reader You’ll need to be comfortable with basic statistics and have an introductory knowledge of R or another high-level programming language. About the author Nina Zumel and John Mount founded a San Francisco–based data science consulting firm. Both hold PhDs from Carnegie Mellon University and blog on statistics, probability, and computer science.




The Case against Education


Book Description

Why we need to stop wasting public funds on education Despite being immensely popular—and immensely lucrative—education is grossly overrated. Now with a new afterword by Bryan Caplan, this explosive book argues that the primary function of education is not to enhance students' skills but to signal the qualities of a good employee. Learn why students hunt for easy As only to forget most of what they learn after the final exam, why decades of growing access to education have not resulted in better jobs for average workers, how employers reward workers for costly schooling they rarely ever use, and why cutting education spending is the best remedy. Romantic notions about education being "good for the soul" must yield to careful research and common sense—The Case against Education points the way.




Learning Statistics with R


Book Description

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com




PC Mag


Book Description

PCMag.com is a leading authority on technology, delivering Labs-based, independent reviews of the latest products and services. Our expert industry analysis and practical solutions help you make better buying decisions and get more from technology.




Spreadsheet Check and Control


Book Description

What other reviewers say about ?Spreadsheet Check and Control??It is excellent. I am embarrassed when I think of the shortcuts I generally take with spreadsheets and I have often paid the price. I think it will become, and it should be, required reading for all young trainee accountants.? Ciaran Walsh, senior finance specialist, Irish Management Institute.?It's super. I kept saying to myself, ?Wow, I didn't know you could do that.? A great job.? Ray Panko, the most cited authority on spreadsheet error, University of Hawai?I.?Spreadsheet Check and Control does what no other book before has attempted to do; provide standards for designing spreadsheets that lend themselves to a logical review by management and internal auditors. Following this author?s guide and insight can help your organization minimize spreadsheet errors and facilitate audit review to prevent and detect those errors.? Jim Kaplan, AuditNet.org.?I thought I knew a lot about Excel, but in the course of teaching me to be Excel-careful, O'Beirne taught me some new tricks and methods that both helped me build better financial models and track down errors.? Simon Benninga, author of Financial Modeling, MIT Press 2000 and Principles of Finance with Excel, Oxford University Press, 2005.'Save red faces all round by buying, absorbing and passing-on this book, especially if you personally develop spreadsheets or if your organization is subject to Sarbanes Oxley and related regulations. Avoiding even a trivial spreadsheet mistake may well pay for the book. Avoiding a large one may save your career.' Dr. Gary Hinson, independent consultant in information security and computer auditing, editor of security awareness website NoticeBored.com.'Probably one of the most important spreadsheet books ever written. Your customers and boss will be delighted with the increased usability, accuracy and reliability his techniques encourage. Be aware that the pages are packed with useful and usable advice, so the 200 pages is probably equivalent to 500 pages in many other books.' Simon Murphy, Codematic.net, author of XLAnalyst.'An essential guide for serious spreadsheet users. This book goes a long way to help spreadsheet users adopt methods that will reduce errors and thereby improve the quality of the information vital to the success of all organisations.' P M Cleary, University of Wales Institute Cardiff, Wales'This is an excellent, easy to follow book containing the key practices that will arm the novice and self taught spreadsheet user so they can create well designed, reliable and error free spreadsheets.' CPA Ireland magazine review'Minimizing or eliminating spreadsheet errors is Patrick O'Beirne's focus in this visual 200-page book, which is geared toward software testers, business managers, or auditors sleuthing for fraud'. CA Magazine (Canada) review Summary of contents