R For Everyone

R for Everyone PDF
Author: Jared P. Lander
Publisher: Addison-Wesley Professional
ISBN: 0134546997
Size: 28.33 MB
Format: PDF
Category : Computers
Languages : en
Pages : 560
View: 6472

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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 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. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write user-defined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and t-tests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via K-means and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available.

R For Everyone

R for Everyone PDF
Author: Jared P. Lander
Publisher: Addison-Wesley Professional
ISBN: 0133257150
Size: 75.83 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 464
View: 6819

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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 non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES • Exploring R, RStudio, and R packages • Using R for math: variable types, vectors, calling functions, and more • Exploiting data structures, including data.frames, matrices, and lists • Creating attractive, intuitive statistical graphics • Writing user-defined functions • Controlling program flow with if, ifelse, and complex checks • Improving program efficiency with group manipulations • Combining and reshaping multiple datasets • Manipulating strings using R’s facilities and regular expressions • Creating normal, binomial, and Poisson probability distributions • Programming basic statistics: mean, standard deviation, and t-tests • Building linear, generalized linear, and nonlinear models • Assessing the quality of models and variable selection • Preventing overfitting, using the Elastic Net and Bayesian methods • Analyzing univariate and multivariate time series data • Grouping data via K-means and hierarchical clustering • Preparing reports, slideshows, and web pages with knitr • Building reusable R packages with devtools and Rcpp • Getting involved with the R global community

Using R For Digital Soil Mapping

Using R for Digital Soil Mapping PDF
Author: Brendan P. Malone
Publisher: Springer
ISBN: 3319443275
Size: 59.44 MB
Format: PDF, ePub
Category : Nature
Languages : en
Pages : 262
View: 3585

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This book describes and provides many detailed examples of implementing Digital Soil Mapping (DSM) using R. The work adheres to Digital Soil Mapping theory, and presents a strong focus on how to apply it. DSM exercises are also included and cover procedures for handling and manipulating soil and spatial data in R. The book also introduces the basic concepts and practices for building spatial soil prediction functions, and then ultimately producing digital soil maps.

Using R For Principles Of Econometrics

Using R for Principles of Econometrics PDF
Author: Constantin Colonescu
Publisher: Lulu.com
ISBN: 1387473611
Size: 25.12 MB
Format: PDF, Mobi
Category : Business & Economics
Languages : en
Pages : 276
View: 936

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This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.

R For Data Science

R for Data Science PDF
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Size: 11.72 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 492
View: 1066

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"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"--

                                      PDF
Author: كارول، لويس،
Publisher:
ISBN: 9789953196381
Size: 20.79 MB
Format: PDF, Kindle
Category :
Languages : ar
Pages : 100
View: 5001

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                PDF
Author: وليم شكسبير
Publisher: ktab INC.
ISBN:
Size: 48.55 MB
Format: PDF, Kindle
Category : Literary Collections
Languages : ar
Pages : 115
View: 2432

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اورلاندو : مخاطبا آدم - لقد اوصى الى ابى بجفنة من المال كما اوعز الى شقيقى بتربيتى تربية حسنة تحت طائلة اللعنة الابوية وقد كان هذا كله مصدرا لاحزانى . فشقيقى ينفق على اخى جاك فى المدرسة ويهتم به لدرجة ان شهرته اصبحت تجوب الافاق - اما انا فانه يعاملنى بخشونة فى المنزل

Niv The Chronological Study Bible Ebook

NIV  The Chronological Study Bible  eBook PDF
Author: Thomas Nelson
Publisher: Thomas Nelson
ISBN: 1401680135
Size: 57.18 MB
Format: PDF, ePub
Category : Bibles
Languages : en
Pages : 1664
View: 5355

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The Chronological Study Bible presents the text of the New International Version in chronological order - the order in which the events actually happened - with notes, articles, and full-color graphics that connect the reader to the history and culture of Bible times and gives the reader a dramatic, "you are there" experience. Features include full-color illustrations of places, artifacts, and cultural phenomena, contextual articles that connect Biblical times and world history and culture, daily life notes, time panels and charts that show the flow of Biblical history, and in-text and full-color maps. Part of the Signature Series line of Thomas Nelson Bibles Chronological Study Bibles sold to date: More than 400,000 Thomas Nelson Bibles is a proud supporter of World Vision in eradicating poverty and preventable deaths among children. Learn more and discover what you can do at www.seegodswordinaction.com.

A Guide To The Project Management Body Of Knowledge Pmbok Guide Fifth Ed Arabic

A Guide to the Project Management Body of Knowledge  Pmbok Guide     Fifth Ed   Arabic  PDF
Author: Project Management Institute
Publisher: Project Management Institute
ISBN: 9781628250008
Size: 15.81 MB
Format: PDF, Kindle
Category : Business & Economics
Languages : en
Pages : 587
View: 1766

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A Guide to the Project Management Body of Knowledge (PMBOK Guide) Fifth Edition reflects the collaboration and knowledge of working project managers and provides the fundamentals of project management as they apply to a wide range of projects. This internationally recognized standard gives project managers the essential tools to practice project management and deliver organizational results. A 10th Knowledge Area has been added; Project Stakeholder Management expands upon the importance of appropriately engaging project stakeholders in key decisions and activities. Project data information and information flow have been redefined to bring greater consistency and be more aligned with the Data, Information, Knowledge and Wisdom (DIKW) model used in the field of Knowledge Management. Four new planning processes have been added: Plan Scope Management, Plan Schedule Management, Plan Cost Management and Plan Stakeholder Management: These were created to reinforce the concept that eac

Modeling Techniques In Predictive Analytics With Python And R

Modeling Techniques in Predictive Analytics with Python and R PDF
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 013389214X
Size: 56.52 MB
Format: PDF
Category : Computers
Languages : en
Pages : 448
View: 7243

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Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Web And Network Data Science

Web and Network Data Science PDF
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133887642
Size: 53.37 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 384
View: 7341

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Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

Modeling Techniques In Predictive Analytics

Modeling Techniques in Predictive Analytics PDF
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133886190
Size: 72.35 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 384
View: 5825

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To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more