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Author : Brian Everitt
Publisher : Unknown
Page : 221 pages
File Size : 41,6 Mb
Release : 2007
Category : Mathematical statistics
ISBN : OCLC:781488894
Author : Brian Everitt
Publisher : Springer Science & Business Media
Page : 231 pages
File Size : 47,7 Mb
Release : 2005-03-17
Category : Computers
ISBN : 9781852338824
Applied statisticians often need to perform analyses of multivariate data; for these they will typically use one of the statistical software packages, S-Plus or R. This book sets out how to use these packages for these analyses in a concise and easy-to-use way, and will save users having to buy two books for the job. The author is well-known for this kind of book, and so buyers will trust that he’s got it right.
Author : Brian S. Everitt
Publisher : Springer Science & Business Media
Page : 232 pages
File Size : 49,9 Mb
Release : 2006-03-30
Category : Mathematics
ISBN : 9781846281242
Applied statisticians often need to perform analyses of multivariate data; for these they will typically use one of the statistical software packages, S-Plus or R. This book sets out how to use these packages for these analyses in a concise and easy-to-use way, and will save users having to buy two books for the job. The author is well-known for this kind of book, and so buyers will trust that he’s got it right.
Author : John Fox
Publisher : SAGE
Page : 332 pages
File Size : 51,7 Mb
Release : 2002-06-05
Category : Mathematics
ISBN : 0761922806
"This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. It meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics, and useful instructions on writing customized functions. " —JEFF GILL, University of Florida, Gainesville
Author : Alain Zuur,Elena N. Ieno,Erik Meesters
Publisher : Springer Science & Business Media
Page : 228 pages
File Size : 48,7 Mb
Release : 2009-06-24
Category : Computers
ISBN : 9780387938370
Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. This book contains everything you need to know to get started with R.
Author : Randall E. Schumacker
Publisher : SAGE Publications
Page : 409 pages
File Size : 45,5 Mb
Release : 2015-06-18
Category : Social Science
ISBN : 9781483377957
Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.
Author : Danney Rasco
Publisher : SAGE Publications
Page : 477 pages
File Size : 41,5 Mb
Release : 2020-06-26
Category : Social Science
ISBN : 9781071815601
An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner′s Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website.
Author : John B.H. Birks,André F. Lotter,Steve Juggins,John P. Smol
Publisher : Springer Science & Business Media
Page : 751 pages
File Size : 53,7 Mb
Release : 2012-04-08
Category : Science
ISBN : 9789400727441
Numerical and statistical methods have rapidly become part of a palaeolimnologist’s tool-kit. They are used to explore and summarise complex data, reconstruct past environmental variables from fossil assemblages, and test competing hypotheses about the causes of observed changes in lake biota through history. This book brings together a wide array of numerical and statistical techniques currently available for use in palaeolimnology and other branches of palaeoecology. Visit http://extras.springer.com the Springer's Extras website to view data-sets, figures, software, and R scripts used or mentioned in this book.
Author : H. John B. Birks,André F. Lotter,Steve Juggins,John P. Smol
Publisher : Springer Science & Business Media
Page : 751 pages
File Size : 53,7 Mb
Release : 2012-04-06
Category : Science
ISBN : 9789400727458
Numerical and statistical methods have rapidly become part of a palaeolimnologist’s tool-kit. They are used to explore and summarise complex data, reconstruct past environmental variables from fossil assemblages, and test competing hypotheses about the causes of observed changes in lake biota through history. This book brings together a wide array of numerical and statistical techniques currently available for use in palaeolimnology and other branches of palaeoecology. Visit http://extras.springer.com the Springer's Extras website to view data-sets, figures, software, and R scripts used or mentioned in this book.
Author : Brian S. Everitt
Publisher : CRC Press
Page : 324 pages
File Size : 50,5 Mb
Release : 2009-09-28
Category : Business & Economics
ISBN : 9781439807705
Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences shows students how to apply statistical methods to behavioral science data in a sensible manner. Assuming some familiarity with introductory statistics, the book analyzes a host of real-world data to provide useful answers to real-life issues.The author begins by exploring
Author : John Fox,Sanford Weisberg
Publisher : SAGE Publications
Page : 608 pages
File Size : 43,6 Mb
Release : 2018-09-27
Category : Social Science
ISBN : 9781544336480
An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials. The Third Edition includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the car and effects packages for R for this new edition, and include coverage of RStudio and R Markdown.
Author : Jason W. Osborne
Publisher : SAGE
Page : 609 pages
File Size : 50,5 Mb
Release : 2008
Category : Social Science
ISBN : 9781412940658
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Author : Muhammad Aslam,Muhammad Imdad Ullah
Publisher : Springer Nature
Page : 300 pages
File Size : 45,7 Mb
Release : 2023-07-19
Category : Computers
ISBN : 9789819928866
This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R. The book also covers flow control and conditional calculations by using ‘‘if’’ conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them.
Author : G. Jay Kerns
Publisher : Lulu.com
Page : 388 pages
File Size : 47,5 Mb
Release : 2010-01-10
Category : Education
ISBN : 9780557249794
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
Author : Clemens Reimann,Peter Filzmoser,Robert Garrett,Rudolf Dutter
Publisher : John Wiley & Sons
Page : 380 pages
File Size : 43,8 Mb
Release : 2011-08-31
Category : Science
ISBN : 9781119965282
Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis. Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.
