3rd Еdition. — Chapman and Hall/CRC, 2025. — 388 р. — ISBN-13: 978-1-003-44997-3. A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with...
Apress, 2025. — 222 p. — ISBN 9798868805790. This book is not a comprehensive guide; if that's what you're seeking, you may want to look elsewhere. Instead, it serves as a map, outlining the necessary tools and topics for your research journey. The goal is to build your intuition and provide pointers for where to find more detailed information. The chapters are deliberately...
John Wiley & Sons, Inc., 2021. — 356 p. — ISBN: 978-93-90421-47-3. With widespread and exponential growth of data, people with data science background are in great demand. Data analytics, a subdomain of data science, is meant to turn data into insight and actionable knowledge. Data analytics mainly deals with exploring, visualizing, transforming and modelling data for making...
Springer Cham, 2025. — 363 p. — (Texts in Quantitative Political Analysis). — eBook ISBN 978-3-031-75853-9. Provides an introduction to using R for political science research. Suitable for students with no programming background. Teaches both tidyverse and base R for a solid foundation. This text teaches basic R skills to political science students with no programming...
2nd Edition. — SAGE Publications Ltd, 2023. — 448 p. — ISBN 978-1529753530. Statistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching...
2nd Edition. — Springer Cham, 2024. — 454 p. — (Use R!). — eBook ISBN 978-3-031-76074-7. Introduces the R system, their capabilities required to perform basic numerical and graphical summaries of data. Introduces using R for simulation including Monte Carlo experiments and Bayesian computation. Features a new chapter on data frames, as well as new coverage on data mining,...
2nd Edition. — Routledge, 2025. — 321 p. — (Quantitative Methodology Series). — ISBN 978-1-032-61940-8. This new edition provides a step-by-step guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable (“latent”) variables. Although the focus is on simple R code, the book provides updated guidance...
Norwich (U.K.): Vor Press, 2023. — 248 p. —(Серия: Statistics without Mathematics). — ISBN 978-1915500044. Introduction Statistics is a seemingly very mysterious yet necessary subject at graduate level. Many graduate students are required to use statistics to carry out their research, be their study in science, medicine, engineering, business, or social sciences. Most...
2nd Edition. — CRC Press, 2025. — 688 p. — ISBN 9780367553234. Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and...
Independently published, 2024. — 138 р. — (Computer Programming). — ASIN: B0DF3VL19J. Unlock Your Data Science Potential with R Programming! Dive into “R Programming: Mastering Data Science and Statistical Computing” , the ultimate guide to one of the most powerful tools in the world of Data Science. Whether you're a complete beginner or an experienced professional looking to...
2nd Edition. — Springer, 2024. — 245 p. — ISBN-13: 978-981-97-4022-2. This book is structured to encompass both the foundational and specialized aspects of quantitative analysis in geography. The basic content covers descriptive statistical analysis and correlation analysis of geographical data, while the professional content delves into more advanced topics like linear...
2nd Edition: Springer, 2024. — 287 p. — (Quantitative Methods in the Humanities and Social Sciences). — ISBN 978-3-031-62565-7. This book teaches readers to integrate data analysis techniques into humanities research practices using the R programming language. Methods for general-purpose visualization and analysis are introduced first, followed by domain-specific techniques for...
Ginnoha Publishing, Miyazaki Yousuke, Fujisaki Ryousuke, Kashiwagi Kaito. — Independent publication, 2024. — 233 р. — ASIN: B0D9D9LLP1. This comprehensive guide offers 100 practical techniques for writing clean, readable, and maintainable R code. Learn how to leverage the power of the tidyverse ecosystem and master the art of data manipulation using the pipe operator %%....
Springer, 2024. — 324 p. — ISBN-13: 978-9819733842. This book is written for statisticians, data analysts, programmers, researchers, professionals, and general consumers on how to perform different types of statistical data analysis for research purposes using R object-oriented programming language and RStudio integrated development environment (IDE). R is an open-source...
Self-published, 2024 — 45 p. — ASIN B0CQK5XFCV. "50 R Exercises" is a practical manual created for people who want to improve their knowledge of R programming and data analysis and visualisation. Whether you're a beginner looking for a firm foundation or an experienced user looking to expand your knowledge, this book provides a carefully chosen set of 50 tasks that gradually...
No Starch Press, 2024. — 306 р. — ISBN-13: 978-1-7185-0333-5. The R programming language is a remarkably powerful tool for data analysis and visualization, but its steep learning curve can be intimidating for some. If you just want to automate repetitive tasks or visualize your data, without the need for complex math, R for the Rest of Us is for you. Inside you’ll find a crash...
2nd Edition. — Springer Cham, 2024. — 555 p. — eBook ISBN 978-3-031-37865-2. Covers the most fundamental topics in probability and statistics, both theoretical and applied Includes a dedicated R package to learn, practise and use the theory A strong grasp of elementary statistics and probability, along with basic skills in using R, is essential for various scientific...
John Wiley & Sons, Inc, For Dummies, 2024. — 214 p. — ISBN 9781394263448. The easy way to get started coding and analyzing data in the R programming language. Statistical Analysis with R Essentials For Dummies is your reference to all the core concepts about R?the widely used, open-source programming language and data analysis tool. This no-nonsense book gets right to the...
CRC Press / Chapman & Hall, 2024. — 298 p. — (Data Science Series). — ISBN: 978-1-032-63351-0. Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and...
Manning Publications, 2024. — 672 p. — ISBN-13: 978-1633438682. Learn statistics by analyzing professional basketball data! In this action-packed book, you’ll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. In Statistics Slam Dunk you’ll develop a toolbox of R data skills including: Reading...
Springer Cham, 2023. — 477 p. — eBook ISBN: 978-3-031-39129-3. One-stop reference for all aspects of Data Analytics, from deep explanation of the algorithms to their application Theoretical-practical approach introduces concepts, then applies them through exercises that are solved using software Consolidates results of EU-funded EDISON project (Education for Data Intensive...
O’Reilly Media, Inc., 2024. — 98 p. — ISBN 978-1-098-15124-9. Tidying up messy software is a must. And that means breaking up the code to make it more readable, and using guard clauses and helping functions to make it understandable. In this practical guide, author Kent Beck, creator of Extreme Programming and pioneer of software patterns, suggests when and where you might...
2nd Edition. — Springer, 2023. — 172 p. — ISBN 978-3-031-35044-3. This book explains the best practices of the UNCTAD & WTO for trade analysis to the R users community. It shows how to replicate the UNCTAD & WTO's Stata codes in the Practical Guide to Trade Policy Analysis by using R. Applications and exercises are chosen from the Practical Guide to Trade Policy Analysis and...
Springer Singapore, 2023. — 292 p. — ISBN 978-981-99-2885-9. Provides useful exercises and practice problems at the end of each chapter. Features with numbering of each R code line in boxes with comments. Presents a useful list of R packages and functions, grouped in different sections. R Language: Introduction Obtaining and Installing R Language Using R as a Calculator Data...
No Starch Press, 2023. — 264 p. — ISBN-13: 978-1-7185-0309-0. Whether you’re a mathematician, seasoned data scientist, or marketing professional, you’ll find The Shape of Data to be the perfect introduction to the critical interplay between the geometry of data structures and Machine Learning. This book’s extensive collection of case studies (drawn from medicine, education,...
2nd Edition. — O’Reilly Media, Inc., 2023. — 381 p. — ISBN-13: 978-1-098-13494-5. Turn your R code into packages that others can easily install and use. With this fully updated edition, developers and data scientists will learn how to bundle reusable R functions, sample data, and documentation together by applying the package development philosophy used by the team that...
2nd Edition. — O’Reilly Media, Inc., 2023. — 600 p. — ISBN-13: 978-1-492-09740-2. Learn how to use R to turn data into insight, knowledge, and understanding. Ideal for current and aspiring data scientists, this book introduces you to doing data science with R and RStudio, as well as the tidyverse—a collection of R packages designed to work together to make data science fast,...
Pelagic Publishing, 2023. — 384 p. — ISBN 978-1-78427-337-8. Введение в R: анализ и визуализация данных 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...
Springer, 2023. — 197 p. Includes data analytic examples in R. This book offers an introduction to applied statistics through data analysis, integrating statistical computing methods. It covers robust and non-robust descriptive statistics used in each of four bivariate statistical models that are commonly used in research: ANOVA, proportions, regression, and logistic. The text...
SAGE Publications, 2021. — 529 p. — ISBN 978-1-5264-5996-1. This book shows students how to recode data, combine data from different sources, document data, and import data from statistical packages other than R. It explores both qualitative and quantitative data and is packed with a range of supportive learning features such as code examples, overview boxes, images, tables,...
Elsevier, 2023. — 274 p. — eBook ISBN: 9780128126974. In today’s competitive environment, airlines are doing everything they can to improve efficiency and productivity. Productivity and Efficiency Measurement of Airlines: Data Envelopment Analysis using R identifies and explains sources of airline efficiency and helps achieve these goals through the use of state-of-the-art...
O’Reilly Media, Inc., 2016. — 335 p. — ISBN 13: 978-1-491-92261-3. It's much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You'll...
John Wiley & Sons, 2023. — 690 p. — (For Dummies). A deep dive into the programming language of choice for statistics and data. With R All-in-One For Dummies , you get five mini-books in one, offering a complete and thorough resource on the R programming language and a road map for making sense of the sea of data we’re all swimming in. Maybe you’re pursuing a career in data...
Springer Cham, 2022. — 376 p. — eBook ISBN 978-3-031-07155-3. This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply...
O’Reilly Media, Inc., 2022. — 381 p. — ISBN-13: 978-1-492-09648-1. Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible...
2nd Edition. — Apress Media, LLC, 2022. — 527 p. — ISBN 978-1-4842-8155-0. Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software...
3rd Edition. — Manning Publications Co., 2022. — 656 p. — ISBN: 978-1617296055. R is the most powerful tool you can use for statistical analysis. This definitive guide smooths R’s steep learning curve with practical solutions and real-world applications for commercial environments. In R in Action, Third Edition you will learn how to: Set up and install R and RStudio Clean,...
Apress Media LLC, 2022. — 602 p. — ISBN-13 (electronic): 978-1-4842-7924-3. This handy reference book detailing the intricacies of R covers version 4.x features, including numerous and significant changes to syntax, strings, reference counting, grid units, and more. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the...
2nd.ed. - Oxford Press, 2022. - 225p. - ISBN: 0197582753 Single-subject research designs have been used to build evidence to the effective treatment of problems across various disciplines including social work, psychology, psychiatry, medicine, allied health fields, juvenile justice, and special education. SSD for R serves as a guide for those desiring to conduct single-subject...
2nd Edition. — Apress Media LLC, 2022. — 278 p. — ISBN-13: 978-1-4842-7201-5. Use R 4, RStudio, Tidyverse, and Shiny to interrogate and analyze your data, and then use the D3 JavaScript library to format and display that data in an elegant, informative, and interactive way. You will learn how to gather data effectively, and also how to understand the philosophy and...
CRC, 2020. — 243 p. — ISBN 978-1138600812 (hardback), ISBN 978-1138600799 (paperback). Using data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an NBA player’s shots or doing an analysis of the impact of...
Springer, 2021. — 266 p. — ISBN 978-3-030-73479-4. This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to...
Independently published, 2021. — 727 p. — ASIN B09B3WCZRM. 2021-07-15 If there is one thing R is famous and known about, is its graphics capabilities. There are many packages out there for producing plots in R, top amongst which is the base graphics package which comes with R preinstalled. The goal of this book is to explore the nooks and crannies of chart production with base...
Academic Press, 2021. — 275 p. — ISBN 0128207884, 9780128207888. Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical...
Springer, 2021. — 155 p. — ISBN 978-3-030-72964-6. This book takes the reader through real-world examples for how to characterize and measure the productivity and performance of NFPs and education institutions—that is, organisations that produce value for society, which cannot be measured accurately in financial KPIs. It focuses on how best to frame non-profit performance and...
Independently published, 2021. — 1206 p. — ASIN B08TW46GVF. Data wrangling is one of the most important steps in data science and analytics, for it is claimed that it takes between 80% to 90% of an analyst’s time. Data wrangling goes by many names including data munging, data manipulation, data preparation and data transformations. Just as there are many names to data...
Apress Media, LLC., 2020. — 481 p. — e-ISBN 978-1-4842-6053-1. Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data), and new data...
2nd edition. — Springer, 2021. — 476 p. — ISBN 978-3-030-64154-2. This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide...
Springer, 2021. — 357 p. — (Use R!). — ISBN 978-3-030-67310-9. This book covers applications of R to the general discipline of radiation dosimetry and to the specific areas of luminescence dosimetry, luminescence dating, and radiation protection dosimetry. It features more than 90 detailed worked examples of R code fully integrated into the text, with extensive annotations. The...
O’Reilly Media, Inc., 2021. — 372 p. — ISBN 978-1492047384. 2021-04-29: First Release Master the Shiny web framework—and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models...
Apress, 2021. — 348 p. — ISBN 978-1484268759. Want to use the power of R sooner rather than later? Don’t have time to plow through wordy texts and online manuals? Use this book for quick, simple code to get your projects up and running. It includes code and examples applicable to many disciplines. Written in everyday language with a minimum of complexity, each chapter provides...
SAGE Publications Ltd, 2021. — 640 p. — ISBN 978-1-5264-8676-9. his approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it...
Springer, 2021. — 239 p. — (Emerging Topics in Statistics and Biostatistics). — ISBN 978-3-030-67582-0. This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial...
Apress, 2021. — 404 p. — ISBN 978-1484268308. Master the syntax for working with R’s plotting functions in graphics and stats in this easy reference to formatting plots. The approach in Visualizing Data in R 4 toward the application of formatting in ggplot() will follow the structure of the formatting used by the plotting functions in graphics and stats. This book will take...
Bookboon, 2015. — 228 p. — ISBN 978-87-403-1123-5. The book offers an introduction to statistical data analysis applying the free statistical software R, probably the most powerful statistical software today. The analyses are performed and discussed using real data. After a brief description of the statistical software R, important parameters and diagrams of descriptive...
Wiley, 2021. — 365 p. — ISBN 978-1119689706. A unique text that simplifies experimental business design and is dedicated to the R language Business Experiments with R offers a guide and explores the fundamentals of experiment business designs. The book fills a gap in the literature with its discussion of business statistics, addressing issues such as small samples, lack of...
2nd edition. — SAGE Publications Ltd, 2019. — 337 p. — (Spatial Analytics and GIS). — ISBN 978-1-5264-2850-9. This is a new edition of the accessible and student-friendly ′how to′ for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping. The authors, once again, take readers from ‘zero to hero’, updating the now standard...
Amazon.com Services LLC, 2021. — 65 p. This Research description has been designed specifically for all categories of researchers which impressively explores the basic data analysis and graphics using R. This edition will satisfy the intensifying need for all social science research and researchers. It acts as an aid to the researcher to know When, Where, How to use the...
SAGE Publications, 2020. — 537 p. — ISBN 9781544324579. Neil J. Salkind’s bestselling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now the bestselling SPSS and Excel versions are joined by a text for use with the R software, Statistics for People Who (Think...
Sage, 2021. — 424 p. — ISBN: 1544370458. Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline business’s customer survey dataset to...
De Gruyter, 2020. — 474 p. — ISBN 9783110564679. In order best exploit the incredible quantities of data being generated in most diverse disciplines data sciences increasingly gain worldwide importance. The book gives the mathematical foundations to handle data properly. It introduces basics and functionalities of the R programming language which has become the indispensable...
Wiley, 2018. — 320 p. — ISBN 978-1118897157 (hardcover). A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning brings together a wide range of techniques for cleaning textual, numeric or categorical data. This...
Independently published, 2021. — 392 p. — ISBN B08W4GGM72. This courseware is intended to be read as a self-study guide or as a book for R programming training. R is an open-source programming language for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing...
Addison-Wesley Professional, 2019. — 385 p. — (Addison-Wesley Data & Analytics Series) — ISBN 0135133106, 9780135133101. The Foundational Hands-On Skills You Need to Dive into Data Science “Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.” –From the foreword by Jared Lander, series editor Using...
CRC Press, 2020. — 249 p. — ISBN 9781138599635. R Visualizations: Derive Meaning from Data focuses on one of the two major topics of data analytics: data visualization, a.k.a., computer graphics. In the book, major R systems for visualization are discussed, organized by topic and not by system. Anyone doing data analysis will be shown how to use R to generate any of the basic...
CRC Press, 2020. — 365 p. — ISBN: 978-1-003-00669-5 (ebk). Just Enough R! An Interactive Approach to Machine Learning and Analytics presents just enough of the R language, machine learning algorithms, statistical methodology, and analytics for the reader to learn how to find interesting structure in data. The approach might be called “seeing then doing” as it first gives...
John Wiley & Sons, Inc., 2021. — 928 p. — ISBN: 978-1-119-63277-1 (EPUB). Introduces professionals and scientists to statistics and machine learning using the programming language R Written by and for practitioners, this book provides an overall introduction to R, focusing on tools and methods commonly used in data science, and placing emphasis on practice and business use. It...
Springer, 2020. — 217 p. — ISBN: 978-9811575679 (paperback), ISBN: 978-9811575686 (ebook). The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building R programs. As the...
CRC Press, 2021. - 390p. - ISBN: 9780367563837 R Markdown is a powerful tool for combining analysis and reporting into the single document in the spirit of literate programming and reproducible research. Since the birth of the rmarkdown package in early 2014, R Markdown has grown substantially from a package that supports a few output formats (such as HTML, PDF, and Word) to an...
Springer, 2020. — 107 p. — ISBN: 3030564843. This book offers an application-oriented guide to random forests: a statistical learning method extensively used in many fields of application, thanks to its excellent predictive performance, but also to its flexibility, which places few restrictions on the nature of the data used. Indeed, random forests can be adapted to both...
Packt, 2019. — 438 p. — ISBN: 1788629159. Hands-On Time Series Analysis with R: Perform time series analysis and forecasting using R Build efficient forecasting models using traditional time series models and machine learning algorithms. Key Features Perform time series analysis and forecasting using R packages such as Forecast and h2o Develop models and find patterns to create...
CRC, 2020. - 364p. - ISBN: 9780367182557 Learning a computer language like R can be either frustrating, fun, or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward on overcoming them. This book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will...
2nd edition. — CRC Press, 2020. — 352 p. — ISBN: 9780367187330. Praise for the first edition: [This book] reflects the extensive experience and significant contributions of the author to non-linear and non-Gaussian modeling. … [It] is a valuable book, especially with its broad and accessible introduction of models in the state space framework. –Statistics in Medicine What...
2nd Edition. — Apress, 2020. — 439 p. — ISBN13: (electronic): 978-1-4842-5973-3. Program for data analysis using R and learn practical skills to make your work more efficient. This revised book explores how to automate running code and the creation of reports to share your results, as well as writing functions and packages. It includes key R 4 features such as a new color...
Apress, 2020. — 332 p. — ISBN: 1484259459. Get started with an accelerated introduction to the R ecosystem, programming language, and tools including R script and RStudio. Utilizing many examples and projects, this book teaches you how to get data into R and how to work with that data using R. Once grounded in the fundamentals, the rest of Practical R 4 dives into specific...
CRC Press, 2020. — 448 p. — ISBN: 13: 978-1-138-33145-7. The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. It is written for the data analyst who wants to leverage the capabilities of interactive web graphics without having to learn web...
Packt Publishing, 2020. — 317 p. — ISBN: 978-1-78899-683-9. Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and Deepnet Deep learning enables efficient and accurate learning from a massive amount of data. This book will help you overcome a number of challenges using various deep learning...
Guzzler Media LLC, 2019. — 118 p. — ISBN: 978-1696769648. 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...
Packt Publishing, 2019. — 518 p. — ISBN: 978-1-78995-069-4. Over 60 recipes to model and handle real-life biological data using modern libraries from the R ecosystem 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...
Palgrave Macmillan, 2015. — 206 p. — ISBN: 978-1-137-43747-1 (eBook). Quantitative Trading with R offers readers a winning strategy for devising expertly-crafted and workable trading models using the R open-source programming language. Based on the author's own experience as a professor and high-frequency trader, this book provides a step-by-step approach to understanding...
2nd ed. — Manning, 2019. — 448 p. — ISBN: 9781617295874. 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...
Wiley, 2019. — 880 p. — ISBN: 978-1118387986. Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p-value are caused by...
O’Reilly Media, Inc., 2020. — 296 p. — ISBN: 149204637X If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to...
Apress, 2019. — 246 p. — ISBN: 978-1484248935, 1484248937. In this handy, practical book you will cover each concept concisely, with many illustrative examples. You'll be introduced to several R data science packages, with examples of how to use each of them. In this book, you’ll learn about the following APIs and packages that deal specifically with data science applications:...
2nd Edition. — O’Reilly Media, 2019. — 600 p. — ISBN: 1492040681, 978-1492040682. 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...
Apress, 2019. - 365p. - ISBN: 1484244044 2nd.ed This handy reference book detailing the intricacies of R updates the popular first edition by adding R version 3.4 and 3.5 features. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an...
Springer, 2019. — 259 р. — ISBN: 9811358494. Deep Learning with R introduces deep learning and neural networks using the R programming language. The book builds on the understanding of the theoretical and mathematical constructs and enables the reader to create applications on computer vision, natural language processing and transfer learning. Deep learning is a specific...
Apress, 2019. — 638 р. — ISBN: 978-1484228715. Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and...
Addison-Wesley Professional, 2018. — 384 p. — ISBN: 978-0135133101. Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience....
2nd. edition. — SAGE Publications, Ins., 2011. — 472 p. — ISBN13: 978-141297514-8. This is a broad introduction to the R statistical computing environment in the context of applied regression analysis. It is a thoroughly updated edition of John Fox′s bestselling text An R and S-Plus Companion to Applied Regression (SAGE, 2002). The Second Edition is intended as a companion to...
SAGE Publications, 2016. — 224 p. — ISBN: 1452288887. Practical Propensity Score Methods Using R by Walter Leite is a practical book that uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing propensity score analysis with the R statistical language. With a comparison of both well-established and cutting-edge propensity...
Packt Publishing, 2014. — 190 p. — ISBN13: 978-1783554553. R has undergone an explosion of popularity around the world. The wide range of graphs and options for creating high-impact visualizations makes R a highly effective tool for researchers, data analysts, students, and others. This book starts with the basics of R and the principles of creating graphics, focusing on...
Apress, 2019. — 243 p. — ISBN: 9781484241998, EIBN 9781484242001. Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning...
Amazon Digital Services LLC, 2018. — 276 р. The Data Science field is expected to continue growing rapidly over the next several years and Data Scientist is consistently rated as a top career.Data Science with R gives you the necessery theoretical background to start your Data Science journey and shows you how to apply the R programming language through practical examples in...
Springer, 2018. — 573 p. — (Springer Texts in Statistics). — ISBN: 1441901175. This textbook presents an introduction to multiple linear regression, providing real-world data sets and practice problems. A practical working knowledge of applied statistical practice is developed through the use of these data sets and numerous case studies. The authors include a set of practice...
2nd ed. — O’Reilly, 2018. — 444 p. — ASIN B07JPL9K64. This O’Reilly cookbook provides more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly—without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project and includes a...
GeoSpatial, 2018. — 246 p. — ASIN B07HM7LC41. Today, data science is an indispensable tool for any organization, allowing for the analysis and optimization of decisions and strategy. R has become the preferred software for data science, thanks to its open source nature, simplicity, applicability to data analysis, and the abundance of libraries for any type of algorithm. This book...
2nd Edition. — CRC Press, Taylor & Francis Group, 2016. — 634 p. — ISBN: 1498734227. Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series...
SAGE, 2015. — 408 p. — ISBN: 978-1483377964. Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and...
Packt Publishing, 2018. — 376 p. — ISBN: 978-1788624145. Key Features Implement machine learning algorithms to build ensemble-efficient models Explore powerful R packages to create predictive models using ensemble methods Learn to build ensemble models on large datasets using a practical approach Book Description Ensemble techniques are used for combining two or more similar or...
Springer London, 2013. — 182 p. When encountering difficult concepts in computer programming for the first time, many students struggle to find simple explanations in their textbooks. Information can also be hard to find on common mistakes made when implementing algorithms and writing programs. This concise and easy-to-follow textbook/guide provides a student-friendly introduction...
N.Y.: Springer, 2015. — 172 p. We live in the age of data. In the last few years, the methodology of extracting insights from data or "data science" has emerged as a discipline in its own right. The R programming language has become one-stop solution for all types of data analysis. The growing popularity of R is due its statistical roots and a vast open source package library. The...
Packt Publishing, 2017 - 470 p. This step-by-step guide demonstrates how to build simple-to-advanced applications through examples in R using modern tools. R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and...
Wiley-VCH, 2018. — 657 p. — ISBN: 3527715371, 9783527715374. Dieses Buch bietet einen einzigartigen Learning-by-Doing-Ansatz. Sie werden Ihre R-Fähigkeiten erweitern und vertiefen, indem Sie eine Vielzahl von Beispielprojekten aus der Praxis nachvollziehen. Erlernen Sie die Grundlagen von R und RStudio sowie Möglichkeiten der Datenreduktion, des Mapping und der...
New York, USA: Apress Media LLC, 2018. — 152 p. — ISBN: 1484235878 Gain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you’ll learn to specify...
Springer, 2018. — 572 p. — (Use R!). — ISBN: 978-3-319-77645-3. Sound is almost always around us, anywhere, at any time, reaching our ears and stimulating our brains for better or worse. Sound can be the disturbing noise of a drill, a merry little tune sung by a friend, the song of a bird in the morning or a clap of thunder at night. The science of sound, or acoustics, studies...
Packt Publishing, 2018. - 570p. - ISBN: 1788393724 2nd.ed. 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. Frequently the tool of choice for academics, R has spread deep into the private sector and...
Packt Publishing, 2017 . - 366p. - ISBN: 1788621875 Key Features A handy guide to take your understanding of data analysis with R to the next level Real-world projects that focus on problems in finance, network analysis, social media, and more From data manipulation to analysis to visualization in R, this book will teach you everything you need to know about building end-to-end...
Packt Publishing, 2017. — 442 p. — ISBN: 1787124460. Mine valuable insights from your data using popular tools and techniques in R About This Book Understand the basics of data mining and why R is a perfect tool for it. Manipulate your data using popular R packages such as ggplot2, dplyr, and so on to gather valuable business insights from it. Apply effective data mining models...
Springer International Publishing AG, 2017. — 264 p. — ISBN: 3319502700. This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data. Introducing...
Packt Publishing, 2016. — 1783 p. Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining...
Wiley, 2018. — 576 p. — ISBN: 978-1-118-87936-8. This book presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text, and...
SAGE Publications Ltd, 2018. 392p. - ISBN: 978-1473924901 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 readers hoping to: Complete an introductory course in statistics Prepare for more advanced statistical courses Gain the transferable analytical skills needed to...
Packt Publishing, 2018. — 422 p. — ISBN: 978-1788627306. Key Features Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values From Simple Linear Regression to Logistic Regression - this book covers all regression techniques and their implementation in R A complete guide to building...
In Easy Steps Limited, 2018. — 192 p. — ISBN: 978-1840787955. The R language is widely used by statisticians for data analysis, and the popularity of R programming has therefore increased substantially in recent years. The emerging Internet of Things (IoT) gathers increasing amounts of data that can be analyzed to gain useful insights into trends. R for Data Analysis in easy...
New York: Leanpub, 2017. — 468 p. This book covers R software development for building data science tools. This book provides rigorous training in the R language and covers modern software development practices for building tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers. The R Programming Environment...
Wiley, 2018. — 360 p. — (For Dummies). — ISBN: 978-1119446187. Make the most of R’s extensive toolset. R Projects For Dummies offers a unique learn-by-doing approach. You will increase the depth and breadth of your R skillset by completing a wide variety of projects. By using R’s graphics, interactive, and machine learning tools, you’ll learn to apply R’s extensive capabilities...
CreateSpace Independent Publishing, 2016. — 154 p. — ISBN: 1533685010. Learn R Programming Today With This Simple Step-By-Step, Ultimate Beginners Guide 2017! Updated & Improved: June 2017 Do you want to learn R Programming? Do you want a guide that is easy to follow, detailed and written to make the process as effortless as possible? If so, “R: Easy R Programming For...
Sage Publications, 2015. — 360 p. R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical...
John Wiley & Sons, 2017. — 312 p. — ISBN: 9781119282099. A reliable, cost-effective approach to extracting priceless business information from all sources of text. Excavating actionable business insights from data is a complex undertaking, and that complexity is magnified by an order of magnitude when the focus is on documents and other text information. This book takes a...
Amazon Digital Services LLC., 2017. – 254 p. – (Multivariate Analysis Book 02) – ASIN B0754LHRMV. This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component methods (PCMs) in R. The visualization is based on the factoextra R package that we developed for creating...
Packt Publishing, 2014. — 364 p. — ISBN: 1784390860. Learn and explore the fundamentals of data science with R. Familiarize yourself with R programming packages and learn how to utilize them effectively; Learn how to detect different types of data mining sequences; A step-by-step guide to understanding R scripts and the ramifications of your changes. Who This Book Is For If you...
Apress, 2017. — 262 p. — ISBN: 978-1-4842-3143-2. Get an introduction to functional data structures using R and write more effective code and gain performance for your programs. This book teaches you workarounds because data in functional languages is not mutable: for example you’ll learn how to change variable-value bindings by modifying environments, which can be exploited to...
2nd ed. — Packt Publishing, 2017. — 588 p. — ISBN: 978-1787284395. Key Features Apply R to simplify predictive modelling with short and simple code Use machine learning to solve problems ranging from small to big data Build a training and testing dataset, applying different classification methods. Book Description The R language is a powerful open source functional programming...
Packt Publishing, 2016. — 278 p. — ISBN: 978-1-78646-515-3. In this book, we cover not only classical data structures, but also functional data structures. We begin by answering the fundamental question: why data structures? We then move on to cover the relationship between data structures and algorithms, followed by an analysis and evaluation of algorithms. We introduce the...
Packt Publishing, 2017. — 236 p. — ASIN B071VFZFN3. Key Features Develop strategies to speed up your R code Tackle programming problems and explore both functional and object-oriented programming techniques Learn how to address the core problems of programming in R with the most popular R packages for common tasks Book Description R is a powerful tool for statistics, graphics,...
Apress, 2017. — 580 p. — ISBN13: 978-1-4842-2333-8. True EPUB This book is inspired by the Machine Learning Model Building Process Flow, which provides the reader the ability to understand a ML algorithm and apply the entire process of building a ML model from the raw data. This new paradigm of teaching Machine Learning will bring about a radical change in perception for many...
Packt Publishing, 2017. — 448 p. — ISBN: 978-1-78712-139-3. Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers...
2nd.ed. — Packt, 2017. — 523 p. — ISBN: 978-1787124479. Key Features Analyse your data using the popular R packages 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 Book Description This book will show you how you can put your data...
Apress, 2017. — 110 p. — ISBN13: 978-1-4842-2918-7. Learn how to write object-oriented programs in R and how to construct classes and class hierarchies in the three object-oriented systems available in R. This book gives an introduction to object-oriented programming in the R programming language and shows you how to use and apply R in an object-oriented manner. You will then...
Packt Publishing, 2017. — 178 p. — ISBN: 978-1-78646-011-0. Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of R Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Moving from data visualization into deeper,...
Apress, 2017. — 103 p. — ISBN: 978-1484228807. Learn how to manipulate functions and expressions to modify how the R language interprets itself. This book is an introduction to metaprogramming in the R language, so you will write programs to manipulate other programs. Metaprogramming in R shows you how to treat code as data that you can generate, analyze, or modify. R is a very...
Chapman and Hall, 2017. — 206 p. — ISBN: 978-1498797320. "This would be an excellent book for undergraduate, graduate and beyond...The style of writing is easy to read and the author does a good job of adding humor in places. The integration of basic programming in R with the data that is collected for any experiment provides a powerful platform for analysis of data... having...
Amazon Digital Services LLC, 2017. — 251 p. — ASIN B0737Z264F. When it comes to data analysis, data science and data mining, R is one of the most important and used programming languages. This book is meant as an introduction to R and is thought to be a quick reference guide for those who want to start programming in this language. The topics we will deal with are: - R structures,...
Packt Publishing, 2017. — 992 p. — ASIN B072XN54R9. +Sample files Create data mining algorithms About This Book Develop a strong strategy to solve predictive modeling problems using the most popular data mining algorithms Real-world case studies will take you from novice to intermediate to apply data mining techniques Deploy cutting-edge sentiment analysis techniques to...
O’Reilly Media, 2017. — 194 p. — ISBN: 978-1491981658. Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy...
Addison-Wesley Professional, 2017.- 560p. - ISBN: 978-0134546926 2nd Edition Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution....
Packt Publishing, 2017. — 413 p. — ISBN: 978-1787127524. The Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how...
Packt Publishing, 2016. — 398 p. — ISBN: 978-1-78588-116-9. Harness actionable insights from your data with computational statistics and simulations using R Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of Rs powerful ecosystem of packages. R being the most widely used programming language when used with data science can be...
Packt Publishing, 2016. — 452 p. — ISBN: 978-1-78439-081-5. Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques 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...
Amazon Digital Service, 2017. — 562 p. — ASIN B071DTSCPS. This book introduces the reader to the use of R and RStudio as a platform for processing and analyzing financial data. The book covers all necessary knowledge for using R, from its installation in your computer to the organization and development of scripts. For every chapter, the book presents practical and replicable...
Packt Publishing, 2016. — 244 p. — ISBN13: 9781784394004. Master the robust features of R parallel programming to accelerate your data science computations R is one of the most popular programming languages used in data science. Applying R to big data and complex analytic tasks requires the harnessing of scalable compute resources. Mastering Parallel Programming with R presents...
Packt Publishing, 2017. — 217 p. — ISBN: 9781786466457 R programming language—an open source, free, extremely versatile statistical environment, has a potential to fill this gap by providing users with a large variety of highly optimized data processing methods, aggregations, statistical tests, and machine learning algorithms with a relatively user-friendly and easily customizable...
Packt Publishing, 2017. — 1065 p. — ISBN: 978-1-78829-037-1. Master the art of predictive modeling Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines. The power and domain-specificity of R allows...
2nd Edition. — Packt Publishingm, 2017. — 420 p. — ASIN B01N5XJ3O0. Master machine learning techniques with R to deliver insights in complex projects. This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating...
Packt Publishing, 2016. — 228 p. — ISBN13: 9781785280252. Learn how to leverage the power of R for Business Intelligence Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused...
Packt Publishing, 2016. — 582 p. — ISBN: 978-1-78588-977-6. Become an efficient data scientist with R R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to...
Packt, 2015. — 374 p. — ISBN: 978-1-78398-452-7 Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry...
Packt Publishing, 2016. — 154 p. — ISBN13: 9781785286544. With organizations increasingly embedding data science across their enterprise and with management becoming more data-driven it is an urgent requirement for analysts and managers to understand the key concept of data science. The data science concepts discussed in this book will help you make key decisions and solve the...
CRC Press, 2016. — 434 p. — ISBN: 9781498736879. Unlike other books about R, written from the perspective of statistics, R for Programmers: Mastering the Tools is written from the perspective of programmers, providing a channel for programmers with expertise in other programming languages to quickly understand R. The contents are divided into four sections: The first section...
Apress, 2017. — 104 p. — ISBN13: 978-1484227459. Master functions and discover how to write functional programs in R. In this concise book, you'll make your functions pure by avoiding side-effects; you’ll write functions that manipulate other functions, and you’ll construct complex functions using simpler functions as building blocks. In Functional Programming in R, you’ll see...
Packt Publishing, 2017. — 284p. — ASIN B06XTHMMWH. Key Features Understand the basics of R and how they can be applied in various Quantitative Finance scenarios Learn various algorithmic trading techniques and ways to optimize them using the tools available in R. Contain different methods to manage risk and explore trading using Machine Learning. Book Description The role of a...
No Starch Press, 2016. — 832 p. — ISBN13: 978-1-59327-651-5. R is the world's most popular programming language for data analysis and statistical modeling. The Book of R provides an in-depth, beginner-friendly guide to the R language, and teaches you how to use R for common statistical analyses. In The Book of R you'll learn key programming techniques, including how to...
John Wiley & Sons, Inc., 2017. — 466 p. 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...
CreateSpace Independent Publishing Platform, 2016. — 288 p. — ISBN: 1508593213, 9781508593218 Learning a programming language is not an easy work. It requires time, money and desire. You must search an academy or a teacher, achieve coordination with them, or worse, adapt your own time to their class times. You also have to pay the high fees, month to month, and what is even more...
Springer, 2015. — 393 p. — ISBN: 3319214152, 9783319214153 This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in...
O’Reilly, 2011. — 131 p. — ISBN: 9781449309039
This book introduces users to the RStudio Integrated Development Environment (IDE) for using and programming R, the widely used open-source statistical computing environment. RStudio is a separate open-source project that brings many powerful coding tools together into an intuitive, easy-to-learn interface. RStudio runs in all...
O’Reilly Media, Inc., 2017. — 234 p. — ISBN: 1491950781, 9781491950784
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices...
O’Reilly, 2017. — 586. — ISBN: 9781491910399
What exactly is data science? With this book, you’ll gain a clear understanding of this discipline for discovering natural laws in the structure of data. Along the way, you’ll learn how to use the versatile R programming language for data analysis.
Whenever you measure the same thing twice, you get two results—as long as you measure...
CRC Press, 2017. — 394 p. — (R Series). — ISBN: 9781498741903 This book provides a general introduction to the R Commander graphical user interface (GUI) to R for readers who are unfamiliar with R. It is suitable for use as a supplementary text in a basic or intermediate-level statistics course. It is not intended to replace a basic or other statistics text but rather to...
Packt Publishing, 2017. — 288 p. — ISBN: 978-1783551811 The book is the process of extracting useful and high-quality information from text by devising patterns and trends. R provides an extensive ecosystem to mine text through its many frameworks and packages. Starting with basic information about the statistics concepts used in text mining, this book will teach you how to...
2 edition. — A John Wiley & Sons, 2013. — 1076 p. — ISBN10: 0470973927. 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...
Apress, 2016. — 450 p. — ISBN: 1484220765, 9781484220764 EISBN: 9781484220771
Program for data analysis using R and learn practical skills to make your work more efficient. This book covers how to automate running code and the creation of reports to share your results, as well as writing functions and packages. Advanced R is not designed to teach advanced R programming nor to...
Packt Publishing, 2016. — 1123 p. — ISBN: 9781787127340, ASIN: B01MQ4M4VO Build your confidence with R and find out how to solve a huge range of data-related problems Get to grips with some of the most important machine learning techniques being used by data scientists and analysts across industries today Don't just learn – apply your knowledge by following featured practical...
Pearson, 2015. — 480 p. in color. — ISBN: 9780133886559. Now, a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the...
2nd ed. — Wiley, 2014. — 336 p. — ISBN: 1118941098, 9781118941096
A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R.
This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range...
Packt Publishing, 2015. — 174 p. in color. — ISBN: 1785283529, 9781785283529
ggplot2 is one of the most sophisticated and advanced packages of R and its use is constantly growing in the community of R programmers. This book is the perfect starting point for your journey in learning about one of the most refined and widely used plotting tools―ggplot2.
You will start by taking a...
Packt Publishing, 2016. — 416 p. — ISBN: 1784390844, 9781784390846 Data science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages,...
Leanpub, 2016. — 143 p.
This book teaches the fundamental concepts and tools behind reporting modern data analyses in a reproducible manner. As data analyses become increasingly complex, the need for clear and reproducible report writing is greater than ever. The material for this book was developed as part of the industry-leading Johns Hopkins Data Science Specialization.
Leanpub, 2016. — 262 p. This book brings the fundamentals of R programming to you, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization. The skills taught in this book will lay the foundation for you to begin your journey learning data science. See the packages below to obtain datasets, R code files, and video lectures.
2nd ed. — Wiley, 2015. — 432 p. —ISBN: 1119055806, 9781119055839 (EPUB) 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,...
Packt Publishing, 2015. — 348 p. — ISBN: 978-1-78398-254-7. RStudio helps you to manage small to large projects by giving you a multi-functional integrated development environment, combined with the power and flexibility of the R programming language, which is becoming the bridge language of data science for developers and analyst worldwide. Mastering the use of RStudio will...
Packt Publishing, 2015. — 245 p. — ISBN: 178398760X, 9781783987603 This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications. To...
2nd Edition. — Manning Publications, 2015. — 608 p. — ISBN: 978-1617291388. Bonus chapter 23 and source code from this book placed here. 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...
Packt Publishing, 2014. — 285 p. — ISBN: 1783986689, 9781783986682
R is best suited to produce data and visual analytics through customizable scripts and commands, instead of typical statistical tools that provide tick boxes and drop-down menus for users. The book is divided into three parts to help you perform these steps. It starts by providing you with an overview of the...
Columbia University Press, 2014. — 248 p. — ISBN: 9780231166980, e-ISBN: 9780231537049 R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented...
Packt Publishing, 2015. — 176 p. — ISBN: 1783989262 Overcome performance difficulties in R with a range of exciting techniques and solutions About This Book Benchmark and profile R programs to solve performance bottlenecks Combine the ease of use and flexibility of R with the power of big data tools Filled with practical techniques and useful code examples to process large data...
Wiley, 2014. — 320 p. — ISBN: 9781118422540
Written at a readily accessible level, Basic Data Analysis for Time Series with R emphasizes the mathematical importance of collaborative analysis of data used to collect increments of time or space. Balancing a theoretical and practical approach to analyzing data within the context of serial correlation, the book presents a coherent...
Wiley, 2014. — 396 p. — ISBN: 0470384425, 9780470384428 A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing...
Wiley, 2014. — 576 p. — ISBN: 1118391411, 9781118391419 An essential library of basic commands you can copy and paste into R The powerful and open-source statistical programming language R is rapidly growing in popularity, but it requires that you type in commands at the keyboard rather than use a mouse, so you have to learn the language of R. But there is a shortcut, and...
SAGE Publications Ltd, 2012. — 992 p. — ISBN: 1446200450, 9781446200452
The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R. Like its sister textbook, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical...
Addison-Wesley, 2013. — 464 p. — ISBN10: 0-321-88803-0, ISBN13: 978-0-321-88803-7. На англ. языке. Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals. Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for...
Barker T. Pro Data Visualization using R and JavaScript Apress, 2013. — 206 p. — ISBN: 1430258063, 9781430258063 Pro Data Visualization using R and JavaScript makes the R language approachable, and promotes the idea of data gathering and analysis. You'll see how to use R to interrogate and analyze your data, and then use the D3 JavaScript library to format and display that data...
Wrox, 2012. – 618 p. – ISBN: 111816430X, 9781118164303 Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly...
Wiley, 2011. — 384 p. — ISBN: 0470944889, 9780470944882. Practical data design tips from a data visualization expert of the modern age. Data doesn?t decrease it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn?t it be wonderful if we could actually visualize data in such a way that we could maximize its potential...
Publisher: O’Reilly Media 2011 | 122 Pages | ISBN: 1449309925 | It’s tough to argue with R as a high-quality, cross-platform, open source statistical software product—unless you’re in the business of crunching Big Data. This concise book introduces you to several strategies for using R to analyze large datasets. You’ll learn the basics of Snow, Multicore, Parallel, and some...
Комментарии