R Cookbook

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449307264
Total Pages : 438 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis R Cookbook by : Paul Teetor

Download or read book R Cookbook written by Paul Teetor and published by "O'Reilly Media, Inc.". This book was released on 2011-03-03 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author

R Cookbook

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492040630
Total Pages : 600 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis R Cookbook by : JD Long

Download or read book R Cookbook written by JD Long and published by "O'Reilly Media, Inc.". This book was released on 2019-06-21 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data

R for Data Science

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis R for Data Science by : Hadley Wickham

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

R Graphics Cookbook

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449316956
Total Pages : 414 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis R Graphics Cookbook by : Winston Chang

Download or read book R Graphics Cookbook written by Winston Chang and published by "O'Reilly Media, Inc.". This book was released on 2013 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Practical recipes for visualizing data"--Cover.

R Data Visualization Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1783989513
Total Pages : 236 pages
Book Rating : 4.7/5 (839 download)

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Book Synopsis R Data Visualization Cookbook by : Atmajitsinh Gohil

Download or read book R Data Visualization Cookbook written by Atmajitsinh Gohil and published by Packt Publishing Ltd. This book was released on 2015-01-29 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.

R for Data Science Cookbook

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1784392049
Total Pages : 452 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis R for Data Science Cookbook by : Yu-Wei, Chiu (David Chiu)

Download or read book R for Data Science Cookbook written by Yu-Wei, Chiu (David Chiu) and published by Packt Publishing Ltd. This book was released on 2016-07-29 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques About This Book Gain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packages Understand how to apply useful data analysis techniques in R for real-world applications An easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysis Who This Book Is For This book is for those who are already familiar with the basic operation of R, but want to learn how to efficiently and effectively analyze real-world data problems using practical R packages. What You Will Learn Get to know the functional characteristics of R language Extract, transform, and load data from heterogeneous sources Understand how easily R can confront probability and statistics problems Get simple R instructions to quickly organize and manipulate large datasets Create professional data visualizations and interactive reports Predict user purchase behavior by adopting a classification approach Implement data mining techniques to discover items that are frequently purchased together Group similar text documents by using various clustering methods In Detail This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently. The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation is provided, illustrating how to use the “dplyr” and “data.table” packages to efficiently process larger data structures. We also focus on “ggplot2” and show you how to create advanced figures for data exploration. In addition, you will learn how to build an interactive report using the “ggvis” package. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction. By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing data analysis. Style and approach This easy-to-follow guide is full of hands-on examples of data analysis with R. Each topic is fully explained beginning with the core concept, followed by step-by-step practical examples, and concluding with detailed explanations of each concept used.

R Cookbook

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Author :
Publisher : O'Reilly Media
ISBN 13 : 144930737X
Total Pages : 436 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis R Cookbook by : Paul Teetor

Download or read book R Cookbook written by Paul Teetor and published by O'Reilly Media. This book was released on 2011-03-03 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author

ggplot2

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 0387981411
Total Pages : 211 pages
Book Rating : 4.3/5 (879 download)

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Book Synopsis ggplot2 by : Hadley Wickham

Download or read book ggplot2 written by Hadley Wickham and published by Springer Science & Business Media. This book was released on 2009-10-03 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides both rich theory and powerful applications Figures are accompanied by code required to produce them Full color figures

R Bioinformatics Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1789955599
Total Pages : 307 pages
Book Rating : 4.7/5 (899 download)

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Book Synopsis R Bioinformatics Cookbook by : Dan MacLean

Download or read book R Bioinformatics Cookbook written by Dan MacLean and published by Packt Publishing Ltd. This book was released on 2019-10-11 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 60 recipes to model and handle real-life biological data using modern libraries from the R ecosystem Key FeaturesApply modern R packages to handle biological data using real-world examplesRepresent biological data with advanced visualizations suitable for research and publicationsHandle real-world problems in bioinformatics such as next-generation sequencing, metagenomics, and automating analysesBook Description Handling biological data effectively requires an in-depth knowledge of machine learning techniques and computational skills, along with an understanding of how to use tools such as edgeR and DESeq. With the R Bioinformatics Cookbook, you’ll explore all this and more, tackling common and not-so-common challenges in the bioinformatics domain using real-world examples. This book will use a recipe-based approach to show you how to perform practical research and analysis in computational biology with R. You will learn how to effectively analyze your data with the latest tools in Bioconductor, ggplot, and tidyverse. The book will guide you through the essential tools in Bioconductor to help you understand and carry out protocols in RNAseq, phylogenetics, genomics, and sequence analysis. As you progress, you will get up to speed with how machine learning techniques can be used in the bioinformatics domain. You will gradually develop key computational skills such as creating reusable workflows in R Markdown and packages for code reuse. By the end of this book, you’ll have gained a solid understanding of the most important and widely used techniques in bioinformatic analysis and the tools you need to work with real biological data. What you will learnEmploy Bioconductor to determine differential expressions in RNAseq dataRun SAMtools and develop pipelines to find single nucleotide polymorphisms (SNPs) and IndelsUse ggplot to create and annotate a range of visualizationsQuery external databases with Ensembl to find functional genomics informationExecute large-scale multiple sequence alignment with DECIPHER to perform comparative genomicsUse d3.js and Plotly to create dynamic and interactive web graphicsUse k-nearest neighbors, support vector machines and random forests to find groups and classify dataWho this book is for This book is for bioinformaticians, data analysts, researchers, and R developers who want to address intermediate-to-advanced biological and bioinformatics problems by learning through a recipe-based approach. Working knowledge of R programming language and basic knowledge of bioinformatics are prerequisites.

R Data Analysis Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1787125319
Total Pages : 549 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis R Data Analysis Cookbook by : Kuntal Ganguly

Download or read book R Data Analysis Cookbook written by Kuntal Ganguly and published by Packt Publishing Ltd. This book was released on 2017-09-20 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 80 recipes to help you breeze through your data analysis projects using R About This Book Analyse your data using the popular R packages like ggplot2 with ready-to-use and customizable recipes Find meaningful insights from your data and generate dynamic reports A practical guide to help you put your data analysis skills in R to practical use Who This Book Is For This book is for data scientists, analysts and even enthusiasts who want to learn and implement the various data analysis techniques using R in a practical way. Those looking for quick, handy solutions to common tasks and challenges in data analysis will find this book to be very useful. Basic knowledge of statistics and R programming is assumed. What You Will Learn Acquire, format and visualize your data using R Using R to perform an Exploratory data analysis Introduction to machine learning algorithms such as classification and regression Get started with social network analysis Generate dynamic reporting with Shiny Get started with geospatial analysis Handling large data with R using Spark and MongoDB Build Recommendation system- Collaborative Filtering, Content based and Hybrid Learn real world dataset examples- Fraud Detection and Image Recognition In Detail Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data. This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way. By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios. Style and Approach Hands-on recipes to walk through data science challenges using R Your one-stop solution for common and not-so-common pain points while performing real-world problems to execute a series of tasks. Addressing your common and not-so-common pain points, this is a book that you must have on the shelf

Statistical Analysis with R For Dummies

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1119337062
Total Pages : 467 pages
Book Rating : 4.1/5 (193 download)

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Book Synopsis Statistical Analysis with R For Dummies by : Joseph Schmuller

Download or read book Statistical Analysis with R For Dummies written by Joseph Schmuller and published by John Wiley & Sons. This book was released on 2017-03-20 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results. Gets you up to speed on the #1 analytics/data science software tool Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling Shows you how R offers intel from leading researchers in data science, free of charge Provides information on using R Studio to work with R Get ready to use R to crunch and analyze your data—the fast and easy way!

R Statistics Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 178980292X
Total Pages : 440 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis R Statistics Cookbook by : Francisco Juretig

Download or read book R Statistics Cookbook written by Francisco Juretig and published by Packt Publishing Ltd. This book was released on 2019-03-29 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve real-world statistical problems using the most popular R packages and techniques Key FeaturesLearn how to apply statistical methods to your everyday research with handy recipesFoster your analytical skills and interpret research across industries and business verticalsPerform t-tests, chi-squared tests, and regression analysis using modern statistical techniquesBook Description R is a popular programming language for developing statistical software. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical procedures across your organization with the help of cutting-edge statistical tools. You'll start by implementing data modeling, data analysis, and machine learning to solve real-world problems. You'll then understand how to work with nonparametric methods, mixed effects models, and hidden Markov models. This book contains recipes that will guide you in performing univariate and multivariate hypothesis tests, several regression techniques, and using robust techniques to minimize the impact of outliers in data.You'll also learn how to use the caret package for performing machine learning in R. Furthermore, this book will help you understand how to interpret charts and plots to get insights for better decision making. By the end of this book, you will be able to apply your skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are extensively used in the data science industry. What you will learnBecome well versed with recipes that will help you interpret plots with RFormulate advanced statistical models in R to understand its conceptsPerform Bayesian regression to predict models and input missing dataUse time series analysis for modelling and forecasting temporal dataImplement a range of regression techniques for efficient data modellingGet to grips with robust statistics and hidden Markov modelsExplore ANOVA (Analysis of Variance) and perform hypothesis testingWho this book is for If you are a quantitative researcher, statistician, data analyst, or data scientist looking to tackle various challenges in statistics, this book is what you need! Proficiency in R programming and basic knowledge of linear algebra is necessary to follow along the recipes covered in this book.

R Data Analysis Cookbook

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 9781783989072
Total Pages : 342 pages
Book Rating : 4.9/5 (89 download)

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Book Synopsis R Data Analysis Cookbook by : Viswa Viswanathan

Download or read book R Data Analysis Cookbook written by Viswa Viswanathan and published by Packt Publishing Ltd. This book was released on 2015-05-27 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 80 recipes to help you breeze through your data analysis projects using R In Detail Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data. This book empowers you by showing you ways to use R to generate professional analysis reports. It provides examples for various important analysis and machine-learning tasks that you can try out with associated and readily available data. The book also teaches you to quickly adapt the example code for your own needs and save yourself the time needed to construct code from scratch. What You Will Learn perform advanced analyses and create informative and professional charts become proficient in acquiring data from many sources apply supervised and unsupervised data mining techniques use R's features to present analyses professionally Get data into your R environment and prepare it for analysis Perform exploratory data analyses and generate meaningful visualizations of the data Apply several machine-learning techniques for classification and regression Get your hands around large data sets with the help of reduction techniques Extract patterns from time-series data and produce forecasts based on them Learn how to extract actionable information from social network data Implement geospatial analysis Present your analysis convincingly through reports and build an infrastructure to enable others to play with your data Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

The R Book

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 9780470515068
Total Pages : 953 pages
Book Rating : 4.5/5 (15 download)

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Book Synopsis The R Book by : Michael J. Crawley

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.

Data Analysis with R, Second Edition

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1788397339
Total Pages : 555 pages
Book Rating : 4.7/5 (883 download)

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Book Synopsis Data Analysis with R, Second Edition by : Anthony Fischetti

Download or read book Data Analysis with R, Second Edition written by Anthony Fischetti and published by Packt Publishing Ltd. This book was released on 2018-03-28 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn, by example, the fundamentals of data analysis as well as several intermediate to advanced methods and techniques ranging from classification and regression to Bayesian methods and MCMC, which can be put to immediate use. Key Features Analyze your data using R – the most powerful statistical programming language Learn how to implement applied statistics using practical use-cases Use popular R packages to work with unstructured and structured data Book Description Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst. What you will learn Gain a thorough understanding of statistical reasoning and sampling theory Employ hypothesis testing to draw inferences from your data Learn Bayesian methods for estimating parameters Train regression, classification, and time series models Handle missing data gracefully using multiple imputation Identify and manage problematic data points Learn how to scale your analyses to larger data with Rcpp, data.table, dplyr, and parallelization Put best practices into effect to make your job easier and facilitate reproducibility Who this book is for Budding data scientists and data analysts who are new to the concept of data analysis, or who want to build efficient analytical models in R will find this book to be useful. No prior exposure to data analysis is needed, although a fundamental understanding of the R programming language is required to get the best out of this book.

RStudio for R Statistical Computing Cookbook

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 178439694X
Total Pages : 247 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis RStudio for R Statistical Computing Cookbook by : Andrea Cirillo

Download or read book RStudio for R Statistical Computing Cookbook written by Andrea Cirillo and published by Packt Publishing Ltd. This book was released on 2016-04-29 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature About This Book 54 useful and practical tasks to improve working systems Includes optimizing performance and reliability or uptime, reporting, system management tools, interfacing to standard data ports, and so on Offers 10-15 real-life, practical improvements for each user type Who This Book Is For This book is targeted at R statisticians, data scientists, and R programmers. Readers with R experience who are looking to take the plunge into statistical computing will find this Cookbook particularly indispensable. What You Will Learn Familiarize yourself with the latest advanced R console features Create advanced and interactive graphics Manage your R project and project files effectively Perform reproducible statistical analyses in your R projects Use RStudio to design predictive models for a specific domain-based application Use RStudio to effectively communicate your analyses results and even publish them to a blog Put yourself on the frontiers of data science and data monetization in R with all the tools that are needed to effectively communicate your results and even transform your work into a data product In Detail The requirement of handling complex datasets, performing unprecedented statistical analysis, and providing real-time visualizations to businesses has concerned statisticians and analysts across the globe. RStudio is a useful and powerful tool for statistical analysis that harnesses the power of R for computational statistics, visualization, and data science, in an integrated development environment. This book is a collection of recipes that will help you learn and understand RStudio features so that you can effectively perform statistical analysis and reporting, code editing, and R development. The first few chapters will teach you how to set up your own data analysis project in RStudio, acquire data from different data sources, and manipulate and clean data for analysis and visualization purposes. You'll get hands-on with various data visualization methods using ggplot2, and you will create interactive and multidimensional visualizations with D3.js. Additional recipes will help you optimize your code; implement various statistical models to manage large datasets; perform text analysis and predictive analysis; and master time series analysis, machine learning, forecasting; and so on. In the final few chapters, you'll learn how to create reports from your analytical application with the full range of static and dynamic reporting tools that are available in RStudio so that you can effectively communicate results and even transform them into interactive web applications. Style and approach RStudio is an open source Integrated Development Environment (IDE) for the R platform. The R programming language is used for statistical computing and graphics, which RStudio facilitates and enhances through its integrated environment. This Cookbook will help you learn to write better R code using the advanced features of the R programming language using RStudio. Readers will learn advanced R techniques to compute the language and control object evaluation within R functions. Some of the contents are: Accessing an API with R Substituting missing values by interpolation Performing data filtering activities R Statistical implementation for Geospatial data Developing shiny add-ins to expand RStudio functionalities Using GitHub with RStudio Modelling a recommendation engine with R Using R Markdown for static and dynamic reporting Curating a blog through RStudio Advanced statistical modelling with R and RStudio

SAS and R

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Author :
Publisher : CRC Press
ISBN 13 : 1420070592
Total Pages : 325 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis SAS and R by : Ken Kleinman

Download or read book SAS and R written by Ken Kleinman and published by CRC Press. This book was released on 2009-07-21 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: An All-in-One Resource for Using SAS and R to Carry out Common TasksProvides a path between languages that is easier than reading complete documentationSAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, id