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R for Programmers - Dan Zhang - Bog - Taylor & Francis Inc - Plusbog.dk

R for Programmers - Dan Zhang - Bog - Taylor & Francis Inc - Plusbog.dk

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 consists of the basics of R, which explains the advantages of using R, the installation of different versions of R, and the 12 frequently used packages of R. This will help you understand the tool packages, time series packages, and performance monitoring packages of R quickly. The second section discusses the server of R, which examines the communication between R and other programming languages and the application of R as servers. This will help you integrate R with other programming languages and implement the server application of R. The third section discusses databases and big data, which covers the communication between R and various databases, as well as R’s integration with Hadoop. This will help you integrate R with the underlying level of other databases and implement the processing of big data by R, based on Hadoop. The fourth section comprises the appendices, which introduce the installation of Java, various databases, and Hadoop. Because this is a reference book, there is no special sequence for reading all the chapters. You can choose the chapters in which you have an interest. If you are new to R, and you wish to master R comprehensively, simply follow the chapters in sequence.

DKK 625.00
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R for Statistics - Maela Kloareg - Bog - Taylor & Francis Inc - Plusbog.dk

R for Statistics - Maela Kloareg - Bog - Taylor & Francis Inc - Plusbog.dk

Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics includes a number of expanded and additional worked examples. Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R. Focusing on the R software, the first section covers: - - Basic elements of the R software and data processing - Clear, concise visualization of results, using simple and complex graphs - Programming basics: pre-defined and user-created functions - The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including: - - Regression methods - Analyses of variance and covariance - Classification methods - Exploratory multivariate analysis - Clustering methods - Hypothesis tests - After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist. Datasets and all the results described in this book are available on the book’s webpage at http://www.agrocampus-ouest.fr/math/RforStat

DKK 579.00
1

Extending R - John M. (stanford University Chambers - Bog - Taylor & Francis Inc - Plusbog.dk

Extending R - John M. (stanford University Chambers - Bog - Taylor & Francis Inc - Plusbog.dk

Up-to-Date Guidance from One of the Foremost Members of the R Core Team Written by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It presents the core ideas of R, provides programming guidance for projects of all scales, and introduces new, valuable techniques that extend R. The book first describes the fundamental characteristics and background of R, giving readers a foundation for the remainder of the text. It next discusses topics relevant to programming with R, including the apparatus that supports extensions. The book then extends R’s data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages. A reflection of what R is today, this guide explains how to design and organize extensions to R by correctly using objects, functions, and interfaces. It enables current and future users to add their own contributions and packages to R. A 2017 Choice Outstanding Academic Title

DKK 662.00
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R Graphics, Third Edition - Paul Murrell - Bog - Taylor & Francis Inc - Plusbog.dk

R Graphics, Third Edition - Paul Murrell - Bog - Taylor & Francis Inc - Plusbog.dk

This third edition of Paul Murrell’s classic book on using R for graphics represents a major update, with a complete overhaul in focus and scope. It focuses primarily on the two core graphics packages in R - graphics and grid - and has a new section on integrating graphics. This section includes three new chapters: importing external images in to R; integrating the graphics and grid systems; and advanced SVG graphics. The emphasis in this third edition is on having the ability to produce detailed and customised graphics in a wide variety of formats, on being able to share and reuse those graphics, and on being able to integrate graphics from multiple systems. This book is aimed at all levels of R users. For people who are new to R, this book provides an overview of the graphics facilities, which is useful for understanding what to expect from R''s graphics functions and how to modify or add to the output they produce. For intermediate-level R users, this book provides all of the information necessary to perform sophisticated customizations of plots produced in R. For advanced R users, this book contains vital information for producing coherent, reusable, and extensible graphics functions.

DKK 884.00
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Computational Methods for Numerical Analysis with R - Ii Howard - Bog - Taylor & Francis Inc - Plusbog.dk

Computational Methods for Numerical Analysis with R - Ii Howard - Bog - Taylor & Francis Inc - Plusbog.dk

Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code. Every algorithm described is given with a complete function implementation in R, along with examples to demonstrate the function and its use. Computational Methods for Numerical Analysis with R is intended for those who already know R, but are interested in learning more about how the underlying algorithms work. As such, it is suitable for statisticians, economists, and engineers, and others with a computational and numerical background.

DKK 958.00
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Using the R Commander - John D. Fox - Bog - Taylor & Francis Inc - Plusbog.dk

Using the R Commander - John D. Fox - Bog - Taylor & Francis Inc - Plusbog.dk

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 complement it, although it does promote sound statistical practice in the examples. The book should also be useful to individual casual or occasional users of R for whom the standard command-line interface is an obstacle. tinyurl.com/RcmdrBookThe site includes data files used in the book and an errata list. http://socserv.mcmaster.ca/jfox/Books/RCommander/Writing-Rcmdr-Plugins.pdf Writing R Commander Plug-in Packages

DKK 634.00
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The R Student Companion - Brian (university Of Idaho Dennis - Bog - Taylor & Francis Inc - Plusbog.dk

The R Student Companion - Brian (university Of Idaho Dennis - Bog - Taylor & Francis Inc - Plusbog.dk

R is the amazing, free, open-access software package for scientific graphs and calculations used by scientists worldwide. The R Student Companion is a student-oriented manual describing how to use R in high school and college science and mathematics courses. Written for beginners in scientific computation, the book assumes the reader has just some high school algebra and has no computer programming background. The author presents applications drawn from all sciences and social sciences and includes the most often used features of R in an appendix. In addition, each chapter provides a set of computational challenges: exercises in R calculations that are designed to be performed alone or in groups. Several of the chapters explore algebra concepts that are highly useful in scientific applications, such as quadratic equations, systems of linear equations, trigonometric functions, and exponential functions. Each chapter provides an instructional review of the algebra concept, followed by a hands-on guide to performing calculations and graphing in R. R is intuitive, even fun. Fantastic, publication-quality graphs of data, equations, or both can be produced with little effort. By integrating mathematical computation and scientific illustration early in a student’s development, R use can enhance one''s understanding of even the most difficult scientific concepts. While R has gained a strong reputation as a package for statistical analysis, The R Student Companion approaches R more completely as a comprehensive tool for scientific computing and graphing.

DKK 477.00
1

R for Programmers - Dan Zhang - Bog - Taylor & Francis Inc - Plusbog.dk

R for Programmers - Dan Zhang - Bog - Taylor & Francis Inc - Plusbog.dk

After the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and business models. R is widely used in this area, and can be a very powerful tool. The author introduces R applications with cases from his own startup, covering topics like portfolio optimization and risk management.

DKK 727.00
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Creating a Lean R&D System - Terence M (director Barnhart - Bog - Taylor & Francis Inc - Plusbog.dk

Creating a Lean R&D System - Terence M (director Barnhart - Bog - Taylor & Francis Inc - Plusbog.dk

This book lays out the logic of why Lean implementation isn‘t strictly for manufacturing and describes why it can be just as effective in R&D organizations. Terence Barnhart, former senior director of continuous improvement at Pfizer R&D, describes the theoretical and physical underpinnings of creating a Lean transformation in any R&D organization, as exemplified by the Lean transformation initiated within the R&D division of a global pharmaceutical company.

DKK 532.00
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Advanced R, Second Edition - Hadley Wickham - Bog - Taylor & Francis Inc - Plusbog.dk

Advanced R, Second Edition - Hadley Wickham - Bog - Taylor & Francis Inc - Plusbog.dk

Advanced R helps you understand how R works at a fundamental level. It is designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages who want to understand what makes R different and special. This book will teach you the foundations of R; three fundamental programming paradigms (functional, object-oriented, and metaprogramming); and powerful techniques for debugging and optimising your code. By reading this book, you will learn: - - The difference between an object and its name, and why the distinction is important - - - The important vector data structures, how they fit together, and how you can pull them apart using subsetting - - - The fine details of functions and environments - - - The condition system, which powers messages, warnings, and errors - - - The powerful functional programming paradigm, which can replace many for loops - - - The three most important OO systems: S3, S4, and R6 - - - The tidy eval toolkit for metaprogramming, which allows you to manipulate code and control evaluation - - - Effective debugging techniques that you can deploy, regardless of how your code is run - - - How to find and remove performance bottlenecks - The second edition is a comprehensive update: - - New foundational chapters: "Names and values," "Control flow," and "Conditions" - - - comprehensive coverage of object oriented programming with chapters on S3, S4, R6, and how to choose between them - - - Much deeper coverage of metaprogramming, including the new tidy evaluation framework - - - use of new package like rlang (http://rlang.r-lib.org), which provides a clean interface to low-level operations, and purr (http://purrr.tidyverse.org/) for functional programming - - - Use of color in code chunks and figures Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science. He is also the author of R for Data Science (with Garrett Grolemund), R Packages , and ggplot2: Elegant Graphics for Data Analysis . -

DKK 532.00
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Testing R Code - Richard (datacamp Cotton - Bog - Taylor & Francis Inc - Plusbog.dk

Testing R Code - Richard (datacamp Cotton - Bog - Taylor & Francis Inc - Plusbog.dk

Learn how to write R code with fewer bugs. The problem with programming is that you are always one typo away from writing something silly. Likewise with data analysis, a small mistake in your model can lead to a big mistake in your results. Combining the two disciplines means that it is all too easy for a missed minus sign to generate a false prediction that you don’t spot until it’s too late. Testing is the only way to be sure that your code, and your results, are correct. Testing R Code teaches you how to perform development-time testing using the testthat package, allowing you to ensure that your code works as intended. The book also teaches run-time testing using the assertive package; enabling your users to correctly run your code. After beginning with an introduction to testing in R, the book explores more advanced cases such as integrating tests into R packages; testing code that accesses databases; testing C++ code with Rcpp; and testing graphics. Each topic is explained with real-world examples, and has accompanying exercises for readers to practise their skills — only a small amount of experience with R is needed to get started!

DKK 468.00
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Starting Quantitative Analysis with R - Josef Fruehwald - Bog - Taylor & Francis Inc - Plusbog.dk

Starting Quantitative Analysis with R - Josef Fruehwald - Bog - Taylor & Francis Inc - Plusbog.dk

With an emphasis on social science applications, this introductory text shows how to perform quantitative analyses using R. Developed from the author’s short courses, the book helps readers go from raw data to results in a timely manner. Topics are organized based on the logical order of adequate quantitative analysis. The book is suitable for novices with little analysis or programming experience as well as more experienced researchers transitioning to R.

DKK 495.00
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Graphical Data Analysis with R - Antony (university Of Augsburg) Unwin - Bog - Taylor & Francis Inc - Plusbog.dk

Graphical Data Analysis with R - Antony (university Of Augsburg) Unwin - Bog - Taylor & Francis Inc - Plusbog.dk

See How Graphics Reveal Information Graphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages and the R code is available at rosuda.org/GDA. Graphical data analysis is useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modelling output, and presenting results. This book guides you in choosing graphics and understanding what information you can glean from them. It can be used as a primary text in a graphical data analysis course or as a supplement in a statistics course. Colour graphics are used throughout.

DKK 745.00
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Analyzing Health Data in R for SAS Users - Monika Maya (laboure College Wahi - Bog - Taylor & Francis Inc - Plusbog.dk

Analyzing Health Data in R for SAS Users - Monika Maya (laboure College Wahi - Bog - Taylor & Francis Inc - Plusbog.dk

Analyzing Health Data in R for SAS Users is aimed at helping health data analysts who use SAS accomplish some of the same tasks in R. It is targeted to public health students and professionals who have a background in biostatistics and SAS software, but are new to R. For professors, it is useful as a textbook for a descriptive or regression modeling class, as it uses a publicly-available dataset for examples, and provides exercises at the end of each chapter. For students and public health professionals, not only is it a gentle introduction to R, but it can serve as a guide to developing the results for a research report using R software. Features : - - Gives examples in both SAS and R - - - Demonstrates descriptive statistics as well as linear and logistic regression - - - Provides exercise questions and answers at the end of each chapter - - - Uses examples from the publicly available dataset, Behavioral Risk Factor Surveillance System (BRFSS) 2014 data - - - Guides the reader on producing a health analysis that could be published as a research report - - - Gives an example of hypothesis-driven data analysis - - - Provides examples of plots with a color insert -

DKK 884.00
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Using R and RStudio for Data Management, Statistical Analysis, and Graphics - Nicholas J. Horton - Bog - Taylor & Francis Inc - Plusbog.dk

Using R and RStudio for Data Management, Statistical Analysis, and Graphics - Nicholas J. Horton - Bog - Taylor & Francis Inc - Plusbog.dk

Improve Your Analytical Skills Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book’s simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information. New to the Second Edition - - The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows - New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics - New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping - New chapter on simulation that includes examples of data generated from complex models and distributions - A detailed discussion of the philosophy and use of the knitr and markdown packages for R - New packages that extend the functionality of R and facilitate sophisticated analyses - Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots - Easily Find Your Desired Task Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.

DKK 778.00
1

60-Minute CEO - Dick Cross - Bog - Taylor & Francis Inc - Plusbog.dk

60-Minute CEO - Dick Cross - Bog - Taylor & Francis Inc - Plusbog.dk

Looking toward the C-suite? Take heed. Author and serial CEO Dick Cross pulls back the curtain on this top leadership role, explaining in his new book that being a successful leader, running a business, and doing it extraordinarily well isn''t a full-time job. In 60-Minute CEO: The Fast Track to Top Leadership, Cross makes the case that the single greatest determinant of business success revolves around the job at the top. Cross suggests that the most important, and often overlooked, duty for a CEO is thinking about how to improve his or her business and how to be a leader. Cross also reveals that a mediocre leader can be transformed into an exemplary one simply by refining two key things: thinking and character. In Cross''s trademark conversational style, he conveys why strategy and execution, while important, should take a back seat to authenticity and responsibility, and that the essential elements of the CEO role can be accomplished in several 60-minute sessions every week. Executives may fill their time with other tasks, but leading and running a company requires explicit skills different from those needed for any other corporate position. The good news is that those skills are easy to learn, fun to do, and not time-consuming. In an entertaining style, Cross offers executives the fast track to the top leadership position. And while 60 minutes may seem like a quick fix, as Cross sees it, three 60-minute sessions a week devoted solely to considering your business and your role as leader are crucial to business and leadership success. In 60-Minute CEO, Dick Cross brings over 25 years of experience of transforming companies in various stages of underperformance into industry powerhouses. Cross combines his knowledge and experience with the stories and lessons of preeminent leaders and thinkers including General George Patton and Seattle Seahawks quarterback Russell Wilson.

DKK 311.00
1

Statistics and Data Analysis for Microarrays Using R and Bioconductor - Sorin Draghici - Bog - Taylor & Francis Inc - Plusbog.dk

Statistics and Data Analysis for Microarrays Using R and Bioconductor - Sorin Draghici - Bog - Taylor & Francis Inc - Plusbog.dk

Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on, example-based approach that teaches students the basics of R and microarray technology as well as how to choose and apply the proper data analysis tool to specific problems. New to the Second Edition Completely updated and double the size of its predecessor, this timely second edition replaces the commercial software with the open source R and Bioconductor environments. Fourteen new chapters cover such topics as the basic mechanisms of the cell, reliability and reproducibility issues in DNA microarrays, basic statistics and linear models in R, experiment design, multiple comparisons, quality control, data pre-processing and normalization, Gene Ontology analysis, pathway analysis, and machine learning techniques. Methods are illustrated with toy examples and real data and the R code for all routines is available on an accompanying downloadable resource. With all the necessary prerequisites included, this best-selling book guides students from very basic notions to advanced analysis techniques in R and Bioconductor. The first half of the text presents an overview of microarrays and the statistical elements that form the building blocks of any data analysis. The second half introduces the techniques most commonly used in the analysis of microarray data.

DKK 1014.00
1

Statistical Computing with R, Second Edition - Maria L. (bowling Green State University Rizzo - Bog - Taylor & Francis Inc - Plusbog.dk

Statistical Computing with R, Second Edition - Maria L. (bowling Green State University Rizzo - Bog - Taylor & Francis Inc - Plusbog.dk

Praise for the First Edition: ". . . the book serves as an excellent tutorial on the R language, providing examples that illustrate programming concepts in the context of practical computational problems. The book will be of great interest for all specialists working on computational statistics and Monte Carlo methods for modeling and simulation." – Tzvetan Semerdjiev, Zentralblatt Math Computational statistics and statistical computing are two areas within statistics that may be broadly described as computational, graphical, and numerical approaches to solving statistical problems. Like its bestselling predecessor, Statistical Computing with R, Second Edition covers the traditional core material of these areas with an emphasis on using the R language via an examples-based approach. The new edition is up-to-date with the many advances that have been made in recent years. Features Provides an overview of computational statistics and an introduction to the R computing environment. Focuses on implementation rather than theory. Explores key topics in statistical computing including Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation. Includes new sections, exercises and applications as well as new chapters on resampling methods and programming topics. Includes coverage of recent advances including R Studio, the tidyverse, knitr and ggplot2 Accompanied by online supplements available on GitHub including R code for all the exercises as well as tutorials and extended examples on selected topics. Suitable for an introductory course in computational statistics or for self-study, Statistical Computing with R , Second Edition provides a balanced, accessible introduction to computational statistics and statistical computing. About the Author Maria Rizzo is Professor in the Department of Mathematics and Statistics at Bowling Green State University in Bowling Green, Ohio, where she teaches statistics, actuarial science, computational statistics, statistical programming and data science. Prior to joining the faculty at BGSU in 2006, she was Assistant Professor in the Department of Mathematics at Ohio University in Athens, Ohio. Her main research area is energy statistics and distance correlation. She is the software developer and maintainer of the energy package for R. She also enjoys writing books including a forthcoming joint research monograph on energy statistics.

DKK 727.00
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Foundational and Applied Statistics for Biologists Using R - Ken A. Aho - Bog - Taylor & Francis Inc - Plusbog.dk

Foundational and Applied Statistics for Biologists Using R - Ken A. Aho - Bog - Taylor & Francis Inc - Plusbog.dk

Full of biological applications, exercises, and interactive graphical examples, Foundational and Applied Statistics for Biologists Using R presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts. Assuming only familiarity with algebra and general calculus, the text offers a flexible structure for both introductory and graduate-level biostatistics courses. The first seven chapters address fundamental topics in statistics, such as the philosophy of science, probability, estimation, hypothesis testing, sampling, and experimental design. The remaining four chapters focus on applications involving correlation, regression, ANOVA, and tabular analyses. Unlike classic biometric texts, this book provides students with an understanding of the underlying statistics involved in the analysis of biological applications. In particular, it shows how a solid statistical foundation leads to the correct application of procedures, a clear understanding of analyses, and valid inferences concerning biological phenomena. Web Resource An R package (asbio) developed by the author is available from CRAN . Accessible to those without prior command-line interface experience, this companion library contains hundreds of functions for statistical pedagogy and biological research. The author’s website also includes an overview of R for novices.

DKK 901.00
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Handbook of Educational Measurement and Psychometrics Using R - Okan (university Of Alberta Bulut - Bog - Taylor & Francis Inc - Plusbog.dk

Handbook of Educational Measurement and Psychometrics Using R - Okan (university Of Alberta Bulut - Bog - Taylor & Francis Inc - Plusbog.dk

Currently there are many introductory textbooks on educational measurement and psychometrics as well as R. However, there is no single book that covers important topics in measurement and psychometrics as well as their applications in R. The Handbook of Educational Measurement and Psychometrics Using R covers a variety of topics, including classical test theory; generalizability theory; the factor analytic approach in measurement; unidimensional, multidimensional, and explanatory item response modeling; test equating; visualizing measurement models; measurement invariance; and differential item functioning. - This handbook is intended for undergraduate and graduate students, researchers, and practitioners as a complementary book to a theory-based introductory or advanced textbook in measurement. Practitioners and researchers who are familiar with the measurement models but need to refresh their memory and learn how to apply the measurement models in R, would find this handbook quite fulfilling. Students taking a course on measurement and psychometrics will find this handbook helpful in applying the methods they are learning in class. In addition, instructors teaching educational measurement and psychometrics will find our handbook as a useful supplement for their course.

DKK 764.00
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Linear Models with R - Julian J. (university Of Bath Faraway - Bog - Taylor & Francis Inc - Plusbog.dk

Linear Models with R - Julian J. (university Of Bath Faraway - Bog - Taylor & Francis Inc - Plusbog.dk

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 R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition. New to the Second Edition - - Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality - Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates - Extensive use of the ggplot2 graphics package in addition to base graphics - Like its widely praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using R.

DKK 901.00
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Dynamic Documents with R and knitr - Yihui Xie - Bog - Taylor & Francis Inc - Plusbog.dk

Dynamic Documents with R and knitr - Yihui Xie - Bog - Taylor & Francis Inc - Plusbog.dk

Quickly and Easily Write Dynamic Documents Suitable for both beginners and advanced users, Dynamic Documents with R and knitr, Second Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams, books, blogs, and web pages to virtually any documents related to statistical graphics, computing, and data analysis. The book covers basic applications for beginners while guiding power users in understanding the extensibility of the knitr package. New to the Second Edition - A new chapter that introduces R Markdown v2 - Changes that reflect improvements in the knitr package - New sections on generating tables, defining custom printing methods for objects in code chunks, the C/Fortran engines, the Stan engine, running engines in a persistent session, and starting a local server to serve dynamic documents Boost Your Productivity in Statistical Report Writing and Make Your Scientific Computing with R Reproducible Like its highly praised predecessor, this edition shows you how to improve your efficiency in writing reports. The book takes you from program output to publication-quality reports, helping you fine-tune every aspect of your report.

DKK 764.00
1