Download or read book Introductory R A Beginner s Guide to Data Visualisation Statistical Analysis and Programming in R written by Robert J. Knell and published by Robert Knell. This book was released on 2014-05-14 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Beginner s Guide for Data Analysis using R Programming written by Jeeva Jose and published by KHANNA PUBLISHING HOUSE. This book was released on with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: R programming is an efficient tool for statistical analysis of data. Data science has become critical to each field and the popularity of R is skyrocketing. Organization as large and diverse as Google, Facebook, Microsoft, Bank of America, Ford Motor Company, Mozilla, Thomas Cook, The New York Times, The National Weather Service, Twitter, ANZ Bank, Uber, Airbnb etc . have turned to R for reporting, analyzing and visualization of data, this book is for students and professionals of Mathematics, Statistics, Physics, Chemistry, Biology, Social Science and Medicine, Business, Engineering, Software, Information Technology, Sales, Bio Informatics, Pharmacy and any one, where data needs to be analyzed and represented graphically.

Download or read book The Book of R written by Tilman M. Davies and published by No Starch Press. This book was released on 2016-07-16 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book R For Dummies written by Andrie de Vries and published by John Wiley & Sons. This book was released on 2012-06-06 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the programming language of choice among statisticians and data analysts worldwide Coming to grips with R can be tough, even for seasoned statisticians and data analysts. Enter R For Dummies, the quick, easy way to master all the R you'll ever need. Requiring no prior programming experience and packed with practical examples, easy, step-by-step exercises, and sample code, this extremely accessible guide is the ideal introduction to R for complete beginners. It also covers many concepts that intermediate-level programmers will find extremely useful. Master your R ABCs ? get up to speed in no time with the basics, from installing and configuring R to writing simple scripts and performing simultaneous calculations on many variables Put data in its place ? get to know your way around lists, data frames, and other R data structures while learning to interact with other programs, such as Microsoft Excel Make data dance to your tune ? learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and much more Visualize it ? learn to use R's powerful data visualization features to create beautiful and informative graphical presentations of your data Get statistical ? find out how to do simple statistical analysis, summarize your variables, and conduct classic statistical tests, such as t-tests Expand and customize R ? get the lowdown on how to find, install, and make the most of add-on packages created by the global R community for a wide variety of purposes Open the book and find: Help downloading, installing, and configuring R Tips for getting data in and out of R Ways to use data frames and lists to organize data How to manipulate and process data Advice on fitting regression models and ANOVA Helpful hints for working with graphics How to code in R What R mailing lists and forums can do for you

Download or read book An Introduction to R written by Mark Gardener and published by Pelagic Publishing Ltd. This book was released on 2023-05-23 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modern world is awash with data. The R Project is a statistical environment and programming language that can help to make sense of it all. A huge open-source project, R has become enormously popular because of its power and flexibility. With R you can organise, analyse and visualise data. This clear and methodical book will help you learn how to use R from the ground up, giving you a start in the world of data science. Learning about data is important in many academic and business settings, and R offers a potent and adaptable programming toolbox. The book covers a range of topics, including: importing/exporting data, summarising data, visualising data, managing and manipulating data objects, data analysis (regression, ANOVA and association among others) and programming functions. Regardless of your background or specialty, you'll find this book the perfect primer on data analysis, data visualisation and data management, and a springboard for further exploration.

Download or read book Learn R Programming in 24 Hours written by Alex Nordeen and published by Guru99. This book was released on 2020-10-31 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?

Download or read book The R Book written by Michael J. Crawley and published by John Wiley & Sons. This book was released on 2007-06-13 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book R Programming written by Andy Vickler and published by R Programming. This book was released on 2022-04-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is an open-source statistical environment and programming language that has grown in popularity for data management and analysis in various industries. "R" Programming teaches you all the R you'll ever need in a rapid and painless manner. This accessible tutorial taught you your way around a list with no previous programming expertise and loads of practical examples, step-by-step exercises, and sample code. This book covers the most significant modeling and prediction methods, as well as their applications. Learn how to use R to transform raw data into knowledge, understanding, and insight. This book introduces you to R, RStudio, and the tidyverse, a set of R tools that work together to make data research simple, fluent, and enjoyable. This book is meant to get you practicing data science as fast as possible, even if you have no prior programming expertise. You'll get a comprehensive grasp of the data science cycle and the fundamental tools you'll need to handle the details. R is becoming more well-known by the day, as large institutions embrace it as a standard. Its popularity stems partly from the fact that it is a free tool replacing expensive statistical software products that may take an undue amount of time to master. Furthermore, R allows a user to do complicated statistical analyses with only a few keystrokes, making advanced studies accessible and clear to a broad audience. Learn how to import data, construct and dismantle data objects, traverse R's environment system, develop your own functions, and utilize all of R's programming tools with this book. This book will not only teach you how to program but also how to use R for more than simply displaying and analyzing data. Most of the chapters are written for you to understand statistical data, so if you are a student, this book can guarantee to teach you some basic statistics that will help you get good grades. Interested in statistical computing ? R Programming: Data Analysis and Statistics is a beginner-friendly book. It is written in an accessible way, and deal with the basics as well as more complex problems. No prior statistical knowledge is required. This book may also help more advanced programmers expand their skills. This book is like a friend who advises and guides you on how to use the ggplot2 package for making data visualizations. With this book, you will learn how to get started with data visualization in R. You will learn basic concepts of graphics, and you will also learn how to perform statistical analyses. This book is for everyone who faces a difficult task when trying to make data visualizations using R. It is also for people who are interested in learning more about statistics and graphical techniques. The book also teaches readers how to get started with ggplot2, and it also introduces the basics of R so that readers are aware of the basic commands and functions in R, as well as importing libraries. R has transformed the way statistical modeling approaches are applied, and has become a tool which is commonly used by analysts, programmers and visual artists alike. Its ease of use and flexibility make it an invaluable tool for working with large amounts of data.

Download or read book Statistical Analysis with R written by John M. Quick and published by . This book was released on 2010 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation This is a practical, step by step guide that will help you to quickly become proficient in the data analysis using R. The book is packed with clear examples, screenshots, and code to carry on your data analysis without any hurdle. If you are a data analyst, business or information technology professional, student, educator, researcher, or anyone else who wants to learn to analyze the data effectively then this book is for you. No prior experience with R is necessary. Knowledge of other programming languages, software packages, or statistics may be helpful, but is not required.

Download or read book R Programming written by Daniel Bell and published by . This book was released on 2019-09-30 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is a programming language and software environment for statistical analysis, graphics representation, and reporting. If you are trying to understand the R programming language as a beginner, this short book will give you enough understanding of almost all the concepts of the R language. The author will guide you through examples, how to program in R and how to use R for effective data analysis.Buy your copy Now! Book ObjectivesThis book is about R programming. The following are the objectives of the author: To familiarize you with the basics of R programming language. To help you understand the various fields where R can be applied and its use cases in each field. To equip you with R programming skills, both beginner and advanced skills. To introduce you to R programming for data analysis. To introduce you to R programming for machine learning. To help you understand and appreciate the power of R in statistical computing, data analysis, and scientific research. Who this Book is for? Anybody who is a complete beginner to R Programming. Anybody in need of advancing their R Programming skills. Professionals in computer programming. Professors, lecturers or tutors who are looking to find better ways to explain R programming to their students in the simplest and easiest way. Students and academicians, especially those focusing on R, Data Analysis, Machine Learning, computer science, and Databases development. RequirementsThe author expects you to have a computer installed with an operating system such as Linux, Windows or Mac OS X. What is inside the book? R BASICS R DATA TYPES R VARIABLES AND CONSTANTS R OPERATORS DECISION MAKING IN R R LOOPS R FUNCTIONS R CLASSES AND OBJECTS R FOR DATA SCIENCE R FOR MACHINE LEARNING From the Back Cover.R programming language is one of the most popular languages used by statisticians, data analysts, researchers to retrieve, clean, analyze, visualize and present data. This is a comprehensive book on how to get started with R programming, why you should learn it and how you can learn it. Daniel Bell begins by introducing the readers to the foundations of the R programming language. The aim is to help you understand, how the R interpreter works, the origin of the name R, how to set up the R programming environment, etc. The author has discussed the process of installing R on Windows, Linux and Mac OS. Moreover, the author has explored the basics of R programming including writing comments, using the R console, creating R script files, etc. The various features provided by R have been discussed in depth, including data types, variables, loops, decision making, functions, operators, classes, and objects, etc. The author has also discussed R for data science and R for machine learning. The book has been organized into chapters, with each chapter having many sub-chapters. R code scripts have been provided, alongside thorough explanations of the code and images showing the expected output upon the execution of every script.

Download or read book Statistics with R written by Robert Stinerock and published by SAGE. This book was released on 2018-01-27 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: ***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.

Download or read book R in Action written by Robert I. Kabacoff and published by Simon and Schuster. This book was released on 2015-05-20 with total page 970 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Business pros and researchers thrive on data, and R speaks the language of data analysis. R is a powerful programming language for statistical computing. Unlike general-purpose tools, R provides thousands of modules for solving just about any data-crunching or presentation challenge you're likely to face. R runs on all important platforms and is used by thousands of major corporations and institutions worldwide. About the Book R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing. What's Inside Complete R language tutorial Using R to manage, analyze, and visualize data Techniques for debugging programs and creating packages OOP in R Over 160 graphs About the Author Dr. Rob Kabacoff is a seasoned researcher and teacher who specializes in data analysis. He also maintains the popular Quick-R website at statmethods.net. Table of Contents PART 1 GETTING STARTED Introduction to R Creating a dataset Getting started with graphs Basic data management Advanced data management PART 2 BASIC METHODS Basic graphs Basic statistics PART 3 INTERMEDIATE METHODS Regression Analysis of variance Power analysis Intermediate graphs Resampling statistics and bootstrapping PART 4 ADVANCED METHODS Generalized linear models Principal components and factor analysis Time series Cluster analysis Classification Advanced methods for missing data PART 5 EXPANDING YOUR SKILLS Advanced graphics with ggplot2 Advanced programming Creating a package Creating dynamic reports Advanced graphics with the lattice package available online only from manning.com/kabacoff2

Download or read book Data Visualization written by Kieran Healy and published by Princeton University Press. This book was released on 2018-12-18 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

Download or read book Beginning Data Science in R written by Thomas Mailund and published by Apress. This book was released on 2017-03-09 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. What You Will Learn Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code Who This Book Is For Those with some data science or analytics background, but not necessarily experience with the R programming language.

Download or read book An Introduction to Data Analysis in R written by Alfonso Zamora Saiz and published by Springer. This book was released on 2020-09-24 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.

Download or read book An Introduction to R written by William N. Venables and published by Network Theory.. This book was released on 2002 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a tutorial guide to GNU R, a software environment for statistical computing and graphics.