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R for Political Science Research - Jane L. Sumner - Bog - Springer International Publishing AG - Plusbog.dk

R for Political Science Research - Jane L. Sumner - Bog - Springer International Publishing AG - Plusbog.dk

This text teaches basic R skills to political science students with no programming background. Intended specifically for the students who need to learn R for a class and who have no interest in R or may even be afraid of or hostile to it, this text builds an awareness of basics, confidence, and a skill set necessary to transition into more advanced texts. To that end, in addition to standard topics, this book includes three chapters specific to the new or reluctant learner. The Introduction explicitly sets expectations for how to use the book and discusses fixed and growth mentalities, and why a growth mentality is crucial for learning R. Chapter 1 includes some basic information on programming, R, and their place in political science research. Chapter 2 explicitly discusses errors, warnings, and methods of debugging. Further chapters build on this by including new errors or warnings that students may encounter as they progress. In service of the aim to give students a solid foundation in R and awareness of what it is and can do, this book teaches and uses both tidyverse and base R frameworks throughout. After completing the book, students should be prepared to learn more advanced materials.

DKK 561.00
1

Introduction to Mathematics for Economics with R - Massimiliano Porto - Bog - Springer International Publishing AG - Plusbog.dk

Introduction to Mathematics for Economics with R - Massimiliano Porto - Bog - Springer International Publishing AG - Plusbog.dk

This book provides a practical introduction to mathematics for economics using R software. Using R as a basis, this book guides the reader through foundational topics in linear algebra, calculus, and optimization. The book is organized in order of increasing difficulty, beginning with a rudimentary introduction to R and progressing through exercises that require the reader to code their own functions in R. All chapters include applications for topics in economics and econometrics. As fully reproducible book, this volume gives readers the opportunity to learn by doing and develop research skills as they go. As such, it is appropriate for students in economics and econometrics.

DKK 415.00
1

Political Analysis Using R - James E. Monogan - Bog - Springer International Publishing AG - Plusbog.dk

Political Analysis Using R - James E. Monogan - Bog - Springer International Publishing AG - Plusbog.dk

This book provides a narrative of how R can be useful in the analysis of public administration, public policy, and political science data specifically, in addition to the social sciences more broadly. It can serve as a textbook and reference manual for students and independent researchers who wish to use R for the first time or broaden their skill set with the program. While the book uses data drawn from political science, public administration, and policy analyses, it is written so that students and researchers in other fields should find it accessible and useful as well. By the end of the first seven chapters, an entry-level user should be well acquainted with how to use R as a traditional econometric software program. The remaining four chapters will begin to introduce the user to advanced techniques that R offers but many other programs do not make available such as how to use contributed libraries or write programs in R. The book details how to perform nearly every task routinely associated with statistical modeling: descriptive statistics, basic inferences, estimating common models, and conducting regression diagnostics. For the intermediate or advanced reader, the book aims to open up the wide array of sophisticated methods options that R makes freely available. It illustrates how user-created libraries can be installed and used in real data analysis, focusing on a handful of libraries that have been particularly prominent in political science. The last two chapters illustrate how the user can conduct linear algebra in R and create simple programs. A key point in these chapters will be that such actions are substantially easier in R than in many other programs, so advanced techniques are more accessible in R, which will appeal to scholars and policy researchers who already conduct extensive data analysis. Additionally, the book should draw the attention of students and teachers of quantitative methods in the political disciplines.

DKK 225.00
1

Applied Linear Regression for Business Analytics with R - Daniel P. Mcgibney - Bog - Springer International Publishing AG - Plusbog.dk

Applied Linear Regression for Business Analytics with R - Daniel P. Mcgibney - Bog - Springer International Publishing AG - Plusbog.dk

Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.

DKK 967.00
1

Meta-Analysis with R - Gerta Rucker - Bog - Springer International Publishing AG - Plusbog.dk

Meta-Analysis with R - Gerta Rucker - Bog - Springer International Publishing AG - Plusbog.dk

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 meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.

DKK 497.00
1

Applied Multivariate Statistics with R - Daniel Zelterman - Bog - Springer International Publishing AG - Plusbog.dk

Applied Multivariate Statistics with R - Daniel Zelterman - Bog - Springer International Publishing AG - Plusbog.dk

Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R , Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.

DKK 884.00
1

Latent Variable Analysis and Signal Separation - - Bog - Springer International Publishing AG - Plusbog.dk

Latent Variable Analysis and Signal Separation - - Bog - Springer International Publishing AG - Plusbog.dk

This book constitutes the proceedings of the 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017, held in Grenoble, France, in Feburary 2017. The 53 papers presented in this volume were carefully reviewed and selected from 60 submissions. They were organized in topical sections named: tensor approaches; from source positions to room properties: learning methods for audio scene geometry estimation; tensors and audio; audio signal processing; theoretical developments; physics and bio signal processing; latent variable analysis in observation sciences; ICA theory and applications; and sparsity-aware signal processing.

DKK 426.00
1

Applied Calculus with R - Thomas J. Pfaff - Bog - Springer International Publishing AG - Plusbog.dk

Applied Calculus with R - Thomas J. Pfaff - Bog - Springer International Publishing AG - Plusbog.dk

This textbook integrates scientific programming with the use of R and uses it both as a tool for applied problems and to aid in learning calculus ideas. Adding R, which is free and used widely outside academia, introduces students to programming and expands the types of problems students can engage. There are no expectations that a student has any coding experience to use this text. While this is an applied calculus text including real world data sets, a student that decides to go on in mathematics should develop sufficient algebraic skills so that they can be successful in a more traditional second semester calculus course. Hopefully, the applications provide some motivation to learn techniques and theory and to take additional math courses. The book contains chapters in the appendix for algebra review as algebra skills can always be improved. Exercise sets and projects are included throughout with numerous exercises based on graphs.

DKK 569.00
1

Applied Calculus with R - Thomas J. Pfaff - Bog - Springer International Publishing AG - Plusbog.dk

Applied Calculus with R - Thomas J. Pfaff - Bog - Springer International Publishing AG - Plusbog.dk

This textbook integrates scientific programming with the use of R and uses it both as a tool for applied problems and to aid in learning calculus ideas. Adding R, which is free and used widely outside academia, introduces students to programming and expands the types of problems students can engage. There are no expectations that a student has any coding experience to use this text. While this is an applied calculus text including real world data sets, a student that decides to go on in mathematics should develop sufficient algebraic skills so that they can be successful in a more traditional second semester calculus course. Hopefully, the applications provide some motivation to learn techniques and theory and to take additional math courses. The book contains chapters in the appendix for algebra review as algebra skills can always be improved. Exercise sets and projects are included throughout with numerous exercises based on graphs.

DKK 486.00
1

Introduction to Probability, Statistics & R - Sujit K. Sahu - Bog - Springer International Publishing AG - Plusbog.dk

Introduction to Probability, Statistics & R - Sujit K. Sahu - Bog - Springer International Publishing AG - Plusbog.dk

A strong grasp of elementary statistics and probability, along with basic skills in using R, is essential for various scientific disciplines reliant on data analysis. This book serves as a gateway to learning statistical methods from scratch, assuming a solid background in high school mathematics. Readers gradually progress from basic concepts to advanced statistical modelling, with examples from actuarial, biological, ecological, engineering, environmental, medicine, and social sciences highlighting the real-world relevance of the subject. An accompanying R package enables seamless practice and immediate application, making it ideal for beginners. The book comprises 19 chapters divided into five parts. Part I introduces basic statistics and the R software package, teaching readers to calculate simple statistics and create basic data graphs. Part II delves into probability concepts, including rules and conditional probability, and introduces widelyused discrete and continuous probability distributions (e.g., binomial, Poisson, normal, log-normal). It concludes with the central limit theorem and joint distributions for multiple random variables. Part III explores statistical inference, covering point and interval estimation, hypothesis testing, and Bayesian inference. This part is intentionally less technical, making it accessible to readers without an extensive mathematical background. Part IV addresses advanced probability and statistical distribution theory, assuming some familiarity with (or concurrent study of) mathematical methods like advanced calculus and linear algebra. Finally, Part V focuses on advanced statistical modelling using simple and multiple regression and analysis of variance, laying the foundation for further studies in machine learning and data science applicable to various data and decision analytics contexts. Based on years of teaching experience, this textbook includes numerousexercises and makes extensive use of R, making it ideal for year-long data science modules and courses. In addition to university courses, the book amply covers the syllabus for the Actuarial Statistics 1 examination of the Institute and Faculty of Actuaries in London. It also provides a solid foundation for postgraduate studies in statistics and probability, or a reliable reference for statistics.

DKK 486.00
1

Modern Psychometrics with R - Patrick Mair - Bog - Springer International Publishing AG - Plusbog.dk

Modern Psychometrics with R - Patrick Mair - Bog - Springer International Publishing AG - Plusbog.dk

This textbook describes the broadening methodology spectrum of psychological measurement in order to meet the statistical needs of a modern psychologist. The way statistics is used, and maybe even perceived, in psychology has drastically changed over the last few years; computationally as well as methodologically. R has taken the field of psychology by storm, to the point that it can now safely be considered the lingua franca for statistical data analysis in psychology. The goal of this book is to give the reader a starting point when analyzing data using a particular method, including advanced versions, and to hopefully motivate him or her to delve deeper into additional literature on the method. Beginning with one of the oldest psychometric model formulations, the true score model, Mair devotes the early chapters to exploring confirmatory factor analysis, modern test theory, and a sequence of multivariate exploratory method. Subsequent chapters present special techniques useful for modern psychological applications including correlation networks, sophisticated parametric clustering techniques, longitudinal measurements on a single participant, and functional magnetic resonance imaging (fMRI) data. In addition to using real-life data sets to demonstrate each method, the book also reports each method in three parts-- first describing when and why to apply it, then how to compute the method in R, and finally how to present, visualize, and interpret the results. Requiring a basic knowledge of statistical methods and R software, but written in a casual tone, this text is ideal for graduate students in psychology. Relevant courses include methods of scaling, latent variable modeling, psychometrics for graduate students in Psychology, and multivariate methods in the social sciences.

DKK 593.00
1

Bayes Factors for Forensic Decision Analyses with R - Silvia Bozza - Bog - Springer International Publishing AG - Plusbog.dk

Bayes Factors for Forensic Decision Analyses with R - Silvia Bozza - Bog - Springer International Publishing AG - Plusbog.dk

Bayes Factors for Forensic Decision Analyses with R provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational perspective, practical relevance, and applicability-keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics: - Probabilistic Inference - Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence. - Decision Making - Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law. - Operational Relevance - Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context. Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes'' theorem providing the fundamental logical tenet for assessing how new information-scientific evidence-ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist''s thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty. This book would be relevant to students, practitioners, and applied statisticians interested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes. This book is Open Access.

DKK 415.00
1

Bayes Factors for Forensic Decision Analyses with R - Silvia Bozza - Bog - Springer International Publishing AG - Plusbog.dk

Bayes Factors for Forensic Decision Analyses with R - Silvia Bozza - Bog - Springer International Publishing AG - Plusbog.dk

Bayes Factors for Forensic Decision Analyses with R provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational perspective, practical relevance, and applicability—keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics:Probabilistic Inference - Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence. Decision Making - Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law. Operational Relevance - Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context. Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes' theorem providing the fundamental logical tenet for assessing how new information—scientific evidence—ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist's thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty. This book would be relevant to students, practitioners, and applied statisticiansinterested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes. This book is Open Access.

DKK 328.00
1