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Multivariate Dependencies, Cox, D.R.


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Цена: 24499.00р.
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Автор: Cox, D.R.
Название:  Multivariate Dependencies
ISBN: 9780412754104
Издательство: Taylor&Francis
Классификация:

ISBN-10: 041275410X
Обложка/Формат: Hardback
Страницы: 272
Вес: 0.52 кг.
Дата издания: 01.03.1996
Серия: Chapman & hall/crc monographs on statistics and applied probability
Язык: English
Размер: 240 x 159 x 19
Читательская аудитория: Postgraduate, research & scholarly
Подзаголовок: Models, analysis and interpretation
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Поставляется из: Европейский союз


A Multivariate Claim Count Model for Applications in Insurance

Автор: Selch
Название: A Multivariate Claim Count Model for Applications in Insurance
ISBN: 3319928678 ISBN-13(EAN): 9783319928678
Издательство: Springer
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Цена: 6986.00 р.
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Exploring Multivariate Data with the Forward Search

Автор: Anthony C. Atkinson; Marco Riani; Andrea Cerioli
Название: Exploring Multivariate Data with the Forward Search
ISBN: 1441923535 ISBN-13(EAN): 9781441923530
Издательство: Springer
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Цена: 24456.00 р.
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Описание: This book is concerned with data in which the observations are independent and in which the response is multivariate. Companion book to Robust Diagnostic Regression Analysis (ISBN 0-387-95017) published by Springer in 2000.

Conducting Meta-Analysis Using SAS

Автор: Arthur, Jr.
Название: Conducting Meta-Analysis Using SAS
ISBN: 0805838090 ISBN-13(EAN): 9780805838091
Издательство: Taylor&Francis
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Цена: 6123.00 р.
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Описание: Designed to teach the reader about meta-analysis and show them how to conduct one using SAS. Its focus is more applied and practical than theoretical and will include additional programming codes and examples. Web site to house program code and sample ou

Multivariate Statistical Methods

Автор: Manly Bryan F.J.
Название: Multivariate Statistical Methods
ISBN: 1498728960 ISBN-13(EAN): 9781498728966
Издательство: Taylor&Francis
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Цена: 8726.00 р.
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Описание:

Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used.

The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.

What If There Were No Significance Tests?

Автор: Harlow
Название: What If There Were No Significance Tests?
ISBN: 1138892475 ISBN-13(EAN): 9781138892477
Издательство: Taylor&Francis
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Цена: 10104.00 р.
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Описание: The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways.

Categorical and Nonparametric Data Analysis

Автор: Nussbaum E Michael
Название: Categorical and Nonparametric Data Analysis
ISBN: 1138787825 ISBN-13(EAN): 9781138787827
Издательство: Taylor&Francis
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Цена: 12248.00 р.
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Описание: Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain their assumptions and how tests work in future publications. Numerous examples from psychology, education, and other social sciences demonstrate varied applications of the material. Basic statistics and probability are reviewed for those who need a refresher. Mathematical derivations are placed in optional appendices for those interested in this detailed coverage. Highlights include the following: Unique coverage of categorical and nonparametric statistics better prepares readers to select the best technique for their particular research project; however, some chapters can be omitted entirely if preferred. Step-by-step examples of each test help readers see how the material is applied in a variety of disciplines.  Although the book can be used with any program, examples of how to use the tests in SPSS and Excel foster conceptual understanding. Exploring the Concept boxes integrated throughout prompt students to review key material and draw links between the concepts to deepen understanding.  Problems in each chapter help readers test their understanding of the material.  Emphasis on selecting tests that maximize power helps readers avoid "marginally" significant results.  Website (www.routledge.com/9781138787827) features datasets for the book's examples and problems, and for the instructor, PowerPoint slides, sample syllabi, answers to the even-numbered problems, and Excel data sets for lecture purposes. Intended for individual or combined graduate or advanced undergraduate courses in categorical and nonparametric data analysis, cross-classified data analysis, advanced statistics and/or quantitative techniques taught in psychology, education, human development, sociology, political science, and other social and life sciences, the book also appeals to researchers in these disciplines. The nonparametric chapters can be deleted if preferred. Prerequisites include knowledge of t tests and ANOVA.

Multivariate Dependencies

Автор: Cox, D.R. , Wermuth, Nanny
Название: Multivariate Dependencies
ISBN: 0367401371 ISBN-13(EAN): 9780367401375
Издательство: Taylor&Francis
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Цена: 9798.00 р.
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Описание:

Large observational studies involving research questions that require the measurement of several features on each individual arise in many fields including the social and medical sciences. This book sets out both the general concepts and the more technical statistical issues involved in analysis and interpretation. Numerous illustrative examples are described in outline and four studies are discussed in some detail.

The use of graphical representations of dependencies and independencies among the features under study is stressed, both to incorporate available knowledge at the planning stage of an analysis and to summarize aspects important for interpretation after detailed statistical analysis is complete. This book is aimed at research workers using statistical methods as well as statisticians involved in empirical research.

Modern Statistical Methods for Spatial and Multivariate Data

Автор: Norou Diawara
Название: Modern Statistical Methods for Spatial and Multivariate Data
ISBN: 3030114309 ISBN-13(EAN): 9783030114305
Издательство: Springer
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Цена: 11878.00 р.
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Описание:

This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques.
Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
Multivariate Analysis for the Behavioral Sciences, Second Edition

Автор: Kimmo Vehkalahti , Brian S. Everitt
Название: Multivariate Analysis for the Behavioral Sciences, Second Edition
ISBN: 0815385153 ISBN-13(EAN): 9780815385158
Издательство: Taylor&Francis
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Цена: 13014.00 р.
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Описание: Multivariate Analysis for the Behavioral Sciences, Second Edition is designed to show how a variety of statistical methods can be used to analyse data collected by psychologists and other behavioral scientists.

Multivariate Bonferroni-Type Inequalities

Автор: Chen, John
Название: Multivariate Bonferroni-Type Inequalities
ISBN: 146651843X ISBN-13(EAN): 9781466518438
Издательство: Taylor&Francis
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Цена: 15312.00 р.
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What If There Were No Significance Tests?

Автор: Harlow, Lisa L.
Название: What If There Were No Significance Tests?
ISBN: 1138892467 ISBN-13(EAN): 9781138892460
Издательство: Taylor&Francis
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Цена: 29093.00 р.
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Longitudinal Data Analysis

Автор: Jones, Richard N.
Название: Longitudinal Data Analysis
ISBN: 0415874157 ISBN-13(EAN): 9780415874151
Издательство: Taylor&Francis
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Цена: 8573.00 р.
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