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Applied Multivariate Analysis, Neil H. Timm


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Цена: 12577.00р.
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Автор: Neil H. Timm
Название:  Applied Multivariate Analysis
ISBN: 9781441929631
Издательство: Springer
Классификация:


ISBN-10: 1441929630
Обложка/Формат: Paperback
Страницы: 695
Вес: 1.22 кг.
Дата издания: 29.04.2013
Серия: Springer Texts in Statistics
Язык: English
Размер: 254 x 178 x 37
Основная тема: Mathematics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Univariate statistical analysis is concerned with techniques for the analysis of a single random variable. This book is about applied multivariate analysis. It was written to p- vide students and researchers with an introduction to statistical techniques for the ana- sis of continuous quantitative measurements on several random variables simultaneously. While quantitative measurements may be obtained from any population, the material in this text is primarily concerned with techniques useful for the analysis of continuous obser- tions from multivariate normal populations with linear structure. While several multivariate methods are extensions of univariate procedures, a unique feature of multivariate data an- ysis techniques is their ability to control experimental error at an exact nominal level and to provide information on the covariance structure of the data. These features tend to enhance statistical inference, making multivariate data analysis superior to univariate analysis. While in a previous edition of my textbook on multivariate analysis, I tried to precede a multivariate method with a corresponding univariate procedure when applicable, I have not taken this approach here. Instead, it is assumed that the reader has taken basic courses in multiple linear regression, analysis of variance, and experimental design. While students may be familiar with vector spaces and matrices, important results essential to multivariate analysis are reviewed in Chapter 2. I have avoided the use of calculus in this text.


An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 27712.00 р.
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Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Analysis of Multivariate and High-Dimensional Data

Автор: Koch
Название: Analysis of Multivariate and High-Dimensional Data
ISBN: 0521887933 ISBN-13(EAN): 9780521887939
Издательство: Cambridge Academ
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Цена: 10613.00 р.
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Описание: `Big data` poses challenges that require both classical multivariate methods and modern machine-learning techniques. This coherent treatment integrates theory with data analysis, visualisation and interpretation of the analysis. Problems, data sets and MATLAB (R) code complete the package. It is suitable for master`s/graduate students in statistics and working scientists in data-rich disciplines.

Multivariate Time Series Analysis: With R and Financial Applications

Автор: Ruey S. Tsay
Название: Multivariate Time Series Analysis: With R and Financial Applications
ISBN: 1118617908 ISBN-13(EAN): 9781118617908
Издательство: Wiley
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Цена: 18842.00 р.
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Описание: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series.

The Chicago Guide to Writing about Multivariate Analysis, Second Edition

Автор: Miller Jane E.
Название: The Chicago Guide to Writing about Multivariate Analysis, Second Edition
ISBN: 0226527875 ISBN-13(EAN): 9780226527871
Издательство: Wiley
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Цена: 6653.00 р.
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Описание: Suitable for those who needs to communicate complex research results, this title includes four new chapters that cover writing about interactions, writing about event history analysis, writing about multilevel models, and the "Goldilocks principle" for choosing the right size contrast for interpreting results for different variables.

Applied Multivariate Data Analysis

Автор: J.D. Jobson
Название: Applied Multivariate Data Analysis
ISBN: 1461269474 ISBN-13(EAN): 9781461269472
Издательство: Springer
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Цена: 13974.00 р.
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Описание: A Second Course in Statistics The past decade has seen a tremendous increase in the use of statistical data analysis and in the availability of both computers and statistical software.

Applied Multivariate Analysis

Автор: Ira H. Bernstein; Calvin P. Garbin; Gary K. Teng
Название: Applied Multivariate Analysis
ISBN: 1461387426 ISBN-13(EAN): 9781461387428
Издательство: Springer
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Цена: 14673.00 р.
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Описание: Like most academic authors, my views are a joint product of my teaching and my research. Needless to say, my views reflect the biases that I have acquired. One way to articulate the rationale (and limitations) of my biases is through the preface of a truly great text of a previous era, Cooley and Lohnes (1971, p. v). They draw a distinction between mathematical statisticians whose intel- lect gave birth to the field of multivariate analysis, such as Hotelling, Bartlett, and Wilks, and those who chose to "concentrate much of their attention on methods of analyzing data in the sciences and of interpreting the results of statistical analysis . . . . (and) . . . who are more interested in the sciences than in mathematics, among other characteristics. " I find the distinction between individuals who are temperamentally "mathe- maticians" (whom philosophy students might call "Platonists") and "scientists" ("Aristotelians") useful as long as it is not pushed to the point where one assumes "mathematicians" completely disdain data and "scientists" are never interested in contributing to the mathematical foundations of their discipline. I certainly feel more comfortable attempting to contribute in the "scientist" rather than the "mathematician" role. As a consequence, this book is primarily written for individuals concerned with data analysis. However, as noted in Chapter 1, true expertise demands familiarity with both traditions.


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