Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download R for Data Science PDF full book. Access full book title R for Data Science by Hadley Wickham. Download full books in PDF and EPUB format.
Author: Hadley Wickham Publisher: "O'Reilly Media, Inc." ISBN: 1491910364 Category : Computers Languages : en Pages : 521
Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author: Hadley Wickham Publisher: "O'Reilly Media, Inc." ISBN: 1491910364 Category : Computers Languages : en Pages : 521
Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author: Benjamin S. Baumer Publisher: CRC Press ISBN: 0429575394 Category : Business & Economics Languages : en Pages : 830
Book Description
From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.
Author: Gareth James Publisher: Springer Nature ISBN: 3031387473 Category : Mathematics Languages : en Pages : 617
Book Description
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Author: Jacob Cohen Publisher: Routledge ISBN: 1134742770 Category : Psychology Languages : en Pages : 625
Book Description
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Author: William Edgar Publisher: Crossway ISBN: 1433531690 Category : Religion Languages : en Pages : 754
Book Description
Amid a revival of apologetics, "few things could be more useful than an acquaintance with how Christian faith was defended down through the ages," say the editors in their introduction to this two-part anthology. "Access to both historical and contemporary texts gives us fresh insight into how our fathers in the faith responded to the questions facing them." Volume 2 in this one-of-a-kind resource takes a sweeping look at apologetics from the Reformation to the present. Readings from twenty-six apologists, including Martin Luther, John Calvin, Blaise Pascal, Jonathan Edwards, Søren Kierkegaard, Francis Schaeffer, Alvin Plantinga, and William Lane Craig are included. With editorial commentary and questions for reflection, Christian Apologetics Past and Present will prove a valuable text for students as well as a unique resource for those interested in defending the faith.
Author: Barbara Illowsky Publisher: ISBN: Category : Mathematics Languages : en Pages : 2106
Book Description
Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.
Author: Kenneth J. Moore Publisher: John Wiley & Sons ISBN: 1119436613 Category : Technology & Engineering Languages : en Pages : 966
Book Description
Forages: The Science of Grassland Agriculture, 7th Edition, Volume II will extensively evaluate the current knowledge and information on forage agriculture. Chapters written by leading researchers and authorities in grassland agriculture are aggregated under section themes, each one representing a major topic within grassland science and agriculture. This 7th edition will include two new additional chapters covering all aspects of forage physiology in three separate chapters, instead of one in previous editions. Chapters will be updated throughout to include new information that has developed since the last edition. This new edition of the classic reference serves as a comprehensive supplement to An Introduction to Grassland Agriculture, Volume I.
Author: James A. Henretta Publisher: Bedford/St. Martin's ISBN: 9781457628917 Category : History Languages : en Pages : 0
Book Description
Designed for America’s History, Eighth Edition, this two-volume primary-source reader offers a chorus of voices from the past carefully selected to enrich the study of U.S. history. Five to six documents per chapter, ranging from speeches and political cartoons by celebrated historical figures to personal letters and diary entries by ordinary people, foster historical thinking skills while putting a human face on America’s diverse history. To support the structure of the parent text, unique part document sets at the end of each part present sources that illustrate the major themes of each section. Brief introductions place each document in historical context, and questions for analysis help students practice historical thinking skills and link individual sources to larger themes.
Author: Hadley Wickham
Author: Hadley Wickham
Author: Benjamin S. Baumer
Author: 
Author: Gareth James
Author: Jacob Cohen
Author: William Edgar
Author: Carrell Horton
Author: Barbara Illowsky
Author: Kenneth J. Moore
Author: James A. Henretta