Advanced Statistical Methods

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Understanding Advanced Statistical Methods

Author : Peter Westfall
Publisher : CRC Press
ISBN 13 : 1466512105
Total Pages : 572 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Understanding Advanced Statistical Methods by : Peter Westfall

Download or read book Understanding Advanced Statistical Methods written by Peter Westfall and published by CRC Press. This book was released on 2013-04-09 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.

Advanced Statistical Methods in Data Science

Author : Ding-Geng Chen
Publisher : Springer
ISBN 13 : 9811025940
Total Pages : 222 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Advanced Statistical Methods in Data Science by : Ding-Geng Chen

Download or read book Advanced Statistical Methods in Data Science written by Ding-Geng Chen and published by Springer. This book was released on 2016-11-30 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.

Advanced and Multivariate Statistical Methods

Author : Craig A. Mertler
Publisher : Taylor & Francis
ISBN 13 : 1000480305
Total Pages : 351 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Advanced and Multivariate Statistical Methods by : Craig A. Mertler

Download or read book Advanced and Multivariate Statistical Methods written by Craig A. Mertler and published by Taylor & Francis. This book was released on 2021-11-29 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced and Multivariate Statistical Methods, Seventh Edition provides conceptual and practical information regarding multivariate statistical techniques to students who do not necessarily need technical and/or mathematical expertise in these methods. This text has three main purposes. The first purpose is to facilitate conceptual understanding of multivariate statistical methods by limiting the technical nature of the discussion of those concepts and focusing on their practical applications. The second purpose is to provide students with the skills necessary to interpret research articles that have employed multivariate statistical techniques. Finally, the third purpose of AMSM is to prepare graduate students to apply multivariate statistical methods to the analysis of their own quantitative data or that of their institutions. New to the Seventh Edition All references to SPSS have been updated to Version 27.0 of the software. A brief discussion of practical significance has been added to Chapter 1. New data sets have now been incorporated into the book and are used extensively in the SPSS examples. All the SPSS data sets utilized in this edition are available for download via the companion website. Additional resources on this site include several video tutorials/walk-throughs of the SPSS procedures. These "how-to" videos run approximately 5–10 minutes in length. Advanced and Multivariate Statistical Methods was written for use by students taking a multivariate statistics course as part of a graduate degree program, for example in psychology, education, sociology, criminal justice, social work, mass communication, and nursing.

Understanding and Using Advanced Statistics

Author : Jeremy J Foster
Publisher : SAGE
ISBN 13 : 1412900131
Total Pages : 194 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Understanding and Using Advanced Statistics by : Jeremy J Foster

Download or read book Understanding and Using Advanced Statistics written by Jeremy J Foster and published by SAGE. This book was released on 2006 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: The spread of sophisticated computer packages and the machinery on which to run them has meant that procedures which were previously only available to experienced researchers with access to expensive machines and research students can now be carried out in a few seconds by almost every undergraduate. Understanding and Using Advanced Statistics provides the basis for gaining an understanding of what these analytic procedures do, when they should be used, and what the results provided signify. This comprehensive textbook guides students and researchers through the transition from simple statistics to more complex procedures with accessible language and illustration.

Basic and Advanced Statistical Tests

Author : Amanda Ross
Publisher : Springer
ISBN 13 : 9463510869
Total Pages : 10 pages
Book Rating : 4.4/5 (635 download)

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Book Synopsis Basic and Advanced Statistical Tests by : Amanda Ross

Download or read book Basic and Advanced Statistical Tests written by Amanda Ross and published by Springer. This book was released on 2018-01-03 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on extraction of pertinent information from statistical test outputs, in order to write result sections and/or accompanying tables and/or figures. The book is divided into two encompassing sections: Part I – Basic Statistical Tests and Part II – Advanced Statistical Tests. Part I includes 9 basic statistical tests, and Part II includes 7 advanced statistical tests. Each chapter provides the name of a basic or advanced statistical test, a brief description, examples of when to use each, a sample scenario, and a sample results section write-up. Depending on the test and need, most chapters provide a table and/or figure to accompany the write-up. The purpose of the book is to provide researchers with a reference manual for writing results sections and tables/figures in scholarly works. The authors fill a gap in research support manuals by focusing on sample write-ups and tables/figures for given statistical tests. The book assists researchers by eliminating the need to comb through numerous publications to determine necessary information to report, as well as correct APA format to use, at the close of analyses.

Advanced Statistics in Research

Author : Larry Hatcher
Publisher : Shadow Finch Media LLC
ISBN 13 : 9780985867003
Total Pages : 632 pages
Book Rating : 4.8/5 (67 download)

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Book Synopsis Advanced Statistics in Research by : Larry Hatcher

Download or read book Advanced Statistics in Research written by Larry Hatcher and published by Shadow Finch Media LLC. This book was released on 2013 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results" is the simple, nontechnical introduction to the most complex multivariate statistics presented in empirical research articles. "wwwStatsInResearch.com, " is a companion website that provides free sample chapters, exercises, and PowerPoint slides for students and teachers. A free 600-item test bank is available to instructors. "Advanced Statistics in Research" does not show how to "perform" statistical procedures--it shows how to read, understand, and interpret them, as they are typically presented in journal articles and research reports. It demystifies the sophisticated statistics that stop most readers cold: multiple regression, logistic regression, discriminant analysis, ANOVA, ANCOVA, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more. "Advanced Statistics in Research" assumes that you have never had a course in statistics. It begins at the beginning, with research design, central tendency, variability, z scores, and the normal curve. You will learn (or re-learn) the big-three results that are common to most procedures: statistical significance, confidence intervals, and effect size. Step-by-step, each chapter gently builds on earlier concepts. Matrix algebra is avoided, and complex topics are explained using simple, easy-to-understand examples. "Need help writing up your results?" Advanced Statistics in Research shows how data-analysis results can be summarized in text, tables, and figures according to APA format. You will see how to present the basics (e.g., means and standard deviations) as well as the advanced (e.g., factor patterns, post-hoc tests, path models, and more). "Advanced Statistics in Research" is appropriate as a textbook for graduate students and upper-level undergraduates (see supplementary materials at StatsInResearch.com). It also serves as a handy shelf reference for investigators and all consumers of research.

Statistical Methods

Author : Rudolf J. Freund
Publisher : Elsevier
ISBN 13 : 0080498221
Total Pages : 694 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Statistical Methods by : Rudolf J. Freund

Download or read book Statistical Methods written by Rudolf J. Freund and published by Elsevier. This book was released on 2003-01-07 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters

Advanced Statistics with Applications in R

Author : Eugene Demidenko
Publisher : John Wiley & Sons
ISBN 13 : 1118387988
Total Pages : 880 pages
Book Rating : 4.1/5 (183 download)

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Book Synopsis Advanced Statistics with Applications in R by : Eugene Demidenko

Download or read book Advanced Statistics with Applications in R written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2019-11-12 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said π? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei, and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc. Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the author's website dartmouth.edu/~eugened. This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.

Advanced Statistics for Kinesiology and Exercise Science

Author : Moh H. Malek
Publisher : Routledge
ISBN 13 : 1351864564
Total Pages : 186 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Advanced Statistics for Kinesiology and Exercise Science by : Moh H. Malek

Download or read book Advanced Statistics for Kinesiology and Exercise Science written by Moh H. Malek and published by Routledge. This book was released on 2018-07-17 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Statistics for Kinesiology and Exercise Science is the first textbook to cover advanced statistical methods in the context of the study of human performance. Divided into three distinct sections, the book introduces and explores in depth both analysis of variance (ANOVA) and regressions analyses, including chapters on: preparing data for analysis; one-way, factorial, and repeated-measures ANOVA; analysis of covariance and multiple analyses of variance and covariance; diagnostic tests; regression models for quantitative and qualitative data; model selection and validation; logistic regression Drawing clear lines between the use of IBM SPSS Statistics software and interpreting and analyzing results, and illustrated with sport and exercise science-specific sample data and results sections throughout, the book offers an unparalleled level of detail in explaining advanced statistical techniques to kinesiology students. Advanced Statistics for Kinesiology and Exercise Science is an essential text for any student studying advanced statistics or research methods as part of an undergraduate or postgraduate degree programme in kinesiology, sport and exercise science, or health science.

Design of Experiments and Advanced Statistical Techniques in Clinical Research

Author : Basavarajaiah D. M.
Publisher : Springer Nature
ISBN 13 : 9811582106
Total Pages : 380 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Design of Experiments and Advanced Statistical Techniques in Clinical Research by : Basavarajaiah D. M.

Download or read book Design of Experiments and Advanced Statistical Techniques in Clinical Research written by Basavarajaiah D. M. and published by Springer Nature. This book was released on 2020-11-05 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent Statistical techniques are one of the basal evidence for clinical research, a pivotal in handling new clinical research and in evaluating and applying prior research. This book explores various choices of statistical tools and mechanisms, analyses of the associations among different clinical attributes. It uses advanced statistical methods to describe real clinical data sets, when the clinical processes being examined are still in the process. This book also discusses distinct methods for building predictive and probability distribution models in clinical situations and ways to assess the stability of these models and other quantitative conclusions drawn by realistic experimental data sets. Design of experiments and recent posthoc tests have been used in comparing treatment effects and precision of the experimentation. This book also facilitates clinicians towards understanding statistics and enabling them to follow and evaluate the real empirical studies (formulation of randomized control trial) that pledge insight evidence base for clinical practices. This book will be a useful resource for clinicians, postgraduates scholars in medicines, clinical research beginners and academicians to nurture high-level statistical tools with extensive scope.

Advanced Statistical Methods for the Analysis of Large Data-Sets

Author : Agostino Di Ciaccio
Publisher : Springer Science & Business Media
ISBN 13 : 3642210376
Total Pages : 464 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Advanced Statistical Methods for the Analysis of Large Data-Sets by : Agostino Di Ciaccio

Download or read book Advanced Statistical Methods for the Analysis of Large Data-Sets written by Agostino Di Ciaccio and published by Springer Science & Business Media. This book was released on 2012-03-05 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”

Advanced Statistics for Testing Assumed Causal Relationships

Author : Hooshang Nayebi
Publisher : Springer Nature
ISBN 13 : 303054754X
Total Pages : 125 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Advanced Statistics for Testing Assumed Causal Relationships by : Hooshang Nayebi

Download or read book Advanced Statistics for Testing Assumed Causal Relationships written by Hooshang Nayebi and published by Springer Nature. This book was released on 2020-08-15 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on linear regression, path analysis and logistic regressions, the most used statistical techniques for the test of causal relationships. Its emphasis is on the conceptions and applications of the techniques by using simple examples without requesting any mathematical knowledge. It shows multiple regression analysis accurately reconstructs the causal relationships between phenomena. So, it can be used to test the hypotheses about causal relationships between variables. It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable. It is an advanced statistical text for the graduate students in social and behavior sciences. It also serves as a reference for professionals and researchers.

An Introduction to Intermediate and Advanced Statistical Analyses for Sport and Exercise Scientists

Author : Nikos Ntoumanis
Publisher : John Wiley & Sons
ISBN 13 : 1118962052
Total Pages : 312 pages
Book Rating : 4.1/5 (189 download)

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Book Synopsis An Introduction to Intermediate and Advanced Statistical Analyses for Sport and Exercise Scientists by : Nikos Ntoumanis

Download or read book An Introduction to Intermediate and Advanced Statistical Analyses for Sport and Exercise Scientists written by Nikos Ntoumanis and published by John Wiley & Sons. This book was released on 2016-01-19 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Ntoumanis and Myers have done sport and exercise science researchers and students a tremendous service in producing An Introduction to Intermediate and Advanced Statistical Analyses for Sport and Exercise Scientists. This book has an outstanding compilation of comprehensible chapters dealing with the important concepts and technical minutia of the statistical analyses that sport and exercise science scholars use (or should be using!) in their efforts to conduct meaningful research in the field. It is a resource that all sport and exercise scientists and their students should have on their book shelves." —Robert Eklund, School of Sport, University of Stirling, UK "Motivating, to have a statistics text devoted to enabling researchers studying sport and exercise science to apply the most sophisticated analytical techniques to their data. Authors hit the mark between using technical language as necessary and user-friendly terms or translations to keep users encouraged. Text covers traditional and well-used tools but also less common and more complex tools, but always with familiar examples to make their explanations come alive. As a dynamic systems theorist and developmentalist, I would love to see more researchers in my area create study designs that would enable the use of tools outlined here, such as multilevel structural equation modeling (MSEM) or mediation & moderation analyses, to uncover cascades of relations among subsystems contributing to motor performance, over time. This text can facilitate that outcome." —Beverly D. Ulrich, School of Kinesiology, University of Michigan, USA "The domain of quantitative methods is constantly evolving and expanding. This means that there is tremendous pressure on researchers to stay current, both in terms of best practices and improvements in more traditional methods as well as increasingly complex new methods. With this volume Ntoumanis and Myers present a nice cross-section of both, helping sport and exercise science researchers to address old questions in better ways, and, even more excitingly, to address new questions entirely. I have no doubt that this volume will quickly become a lovingly dog-eared companion for students and researchers, helping them to continue to move the field forward." —Gregory R. Hancock, University of Maryland and Center for Integrated Latent Variable Research (CILVR), USA

Advanced and Multivariate Statistical Methods for Social Science Research

Author : Soleman Hassan Abu-Bader
Publisher : Oxford University Press
ISBN 13 : 0190616393
Total Pages : 377 pages
Book Rating : 4.1/5 (96 download)

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Book Synopsis Advanced and Multivariate Statistical Methods for Social Science Research by : Soleman Hassan Abu-Bader

Download or read book Advanced and Multivariate Statistical Methods for Social Science Research written by Soleman Hassan Abu-Bader and published by Oxford University Press. This book was released on 2010-06 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlike other advanced statistical texts, this book combines the theory and practice behind a number of statistical techniques which students of the social sciences need to evaluate, analyze, and test their research hypotheses. Each chapter discusses the purpose, rationale, and assumptions for using each statistical test, rather than focusing on the memorization of formulas. The tests are further elucidated throughout the text by real examples of analysis. Of particular value to students is the book's detailed discussion of how to utilize SPSS to run each test, read its output, interpret, and write the results. Advanced & Multivariate Statistical Methods for Social Science Research is an indispensable resource for students of disciplines as varied as social work, nursing, public health, psychology, and education. Electronic database files are available for student and instructor use.http: //lyceumbooks.com/StudentResources.htm

Advanced Statistical Mechanics

Author : Jian-sheng Wang
Publisher : World Scientific
ISBN 13 : 981124216X
Total Pages : 225 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Advanced Statistical Mechanics by : Jian-sheng Wang

Download or read book Advanced Statistical Mechanics written by Jian-sheng Wang and published by World Scientific. This book was released on 2021-11-03 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This short textbook covers roughly 13 weeks of lectures on advanced statistical mechanics at the graduate level. It starts with an elementary introduction to the theory of ensembles from classical mechanics, and then goes on to quantum statistical mechanics with density matrix. These topics are covered concisely and briefly. The advanced topics cover the mean-field theory for phase transitions, the Ising models and their exact solutions, and critical phenomena and their scaling theory. The mean-field theories are discussed thoroughly with several different perspectives — focusing on a single degree, or using Feynman-Jensen-Bogoliubov inequality, cavity method, or Landau theory. The renormalization group theory is mentioned only briefly. As examples of computational and numerical approach, there is a chapter on Monte Carlo method including the cluster algorithms. The second half of the book studies nonequilibrium statistical mechanics, which includes the Brownian motion, the Langevin and Fokker-Planck equations, Boltzmann equation, linear response theory, and the Jarzynski equality. The book ends with a brief discussion of irreversibility. The topics are supplemented by problem sets (with partial answers) and supplementary readings up to the current research, such as heat transport with a Fokker-Planck approach.

Advanced Statistics for the Behavioral Sciences

Author : Jonathon D. Brown
Publisher : Springer
ISBN 13 : 9783319935478
Total Pages : 526 pages
Book Rating : 4.9/5 (354 download)

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Book Synopsis Advanced Statistics for the Behavioral Sciences by : Jonathon D. Brown

Download or read book Advanced Statistics for the Behavioral Sciences written by Jonathon D. Brown and published by Springer. This book was released on 2019-05-15 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the importance of computer-generated statistical analyses in behavioral science research, particularly those using the R software environment. Statistical methods are being increasingly developed and refined by computer scientists, with expertise in writing efficient and elegant computer code. Unfortunately, many researchers lack this programming background, leaving them to accept on faith the black-box output that emerges from the sophisticated statistical models they frequently use. Building on the author’s previous volume, Linear Models in Matrix Form, this text bridges the gap between computer science and research application, providing easy-to-follow computer code for many statistical analyses using the R software environment. The text opens with a foundational section on linear algebra, then covers a variety of advanced topics, including robust regression, model selection based on bias and efficiency, nonlinear models and optimization routines, generalized linear models, and survival and time-series analysis. Each section concludes with a presentation of the computer code used to illuminate the analysis, as well as pointers to packages in R that can be used for similar analyses and nonstandard cases. The accessible code and breadth of topics make this book an ideal tool for graduate students or researchers in the behavioral sciences who are interested in performing advanced statistical analyses without having a sophisticated background in computer science and mathematics.

Advanced R Statistical Programming and Data Models

Author : Matt Wiley
Publisher : Apress
ISBN 13 : 1484228723
Total Pages : 649 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Advanced R Statistical Programming and Data Models by : Matt Wiley

Download or read book Advanced R Statistical Programming and Data Models written by Matt Wiley and published by Apress. This book was released on 2019-02-20 with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 concludes with a case study. Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Models shows you how to conduct data analysis using the popular R language. You’ll delve into the preconditions or hypothesis for various statistical tests and techniques and work through concrete examples using R for a variety of these next-level analytics. This is a must-have guide and reference on using and programming with the R language. What You’ll LearnConduct advanced analyses in R including: generalized linear models, generalized additive models, mixed effects models, machine learning, and parallel processing Carry out regression modeling using R data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R including parallel processing, dimension reduction, and feature selection and classification Address missing data using multiple imputation in R Work on factor analysis, generalized linear mixed models, and modeling intraindividual variability Who This Book Is For Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to perform more advanced analytics. Particularly, researchers and data analysts in the social sciences may benefit from these techniques. Additionally, analysts who need parallel processing to speed up analytics are given proven code to reduce time to result(s).