Multivariate applications in the social sciences
Publisher: Lawrence Erlbaum Associates in Hillsdale, N.J
Written in English
- Psychology -- Statistical methods,
- Multivariate analysis,
- Social sciences -- Statistical methods
Includes bibliographies and indexes.
|Statement||edited by Nancy Hirschberg, Lloyd G. Humphreys.|
|Contributions||Hirschberg, Nancy., Humphreys, Lloyd G.|
|LC Classifications||BF39 .M849 1982|
|The Physical Object|
|Pagination||vi, 298 p. :|
|Number of Pages||298|
|LC Control Number||82005069|
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Hirschberg & L. Humphreys. $; $; Publisher Description. First published in Routledge is an imprint of Taylor & Francis, an informa company. Multivariate Applications in the Social Sciences book. DOI link for Multivariate Applications in the Social Sciences. Multivariate Applications in the Social Sciences book.
Edited By N. Hirschberg, L. Humphreys. Edition 1st Edition Cited by: First published in Routledge is an imprint of Taylor & Francis, an informa company. Get this from a library. Multivariate applications in the social sciences. [Nancy Hirschberg;].
Multivariate Applications in the Social Sciences book. DOI link for Multivariate Applications in the Social Sciences. Multivariate Applications in the Social Sciences book. Edited By N. Hirschberg, L. Humphreys. Edition 1st Edition. First Published eBook Published 14 January Author: Lawrence E. Jones.
Multivariate Analysis of Variance (Quantitative Applications in the Social Sciences Book 54) - Kindle edition by Bray, James H., Maxwell, Scott E. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like Multivariate applications in the social sciences book, note taking and highlighting while reading Multivariate Analysis of Variance (Quantitative Applications in the Social Sciences Book 54).5/5(1).
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The book looks at multivariate time series and plots tests of them a bid too short. The variables used are not described well (MFD for example is not explained Cited by: In most chapters, the authors present suggestions for further work that go beyond conventional exercises, encouraging readers to explore new ground in social science research.
Requiring minimal mathematical and statistical knowledge, this book shows how various multivariate methods reveal different aspects of data and thus help answer. Multivariate Analysis Techniques in Social Science Research (J. Tacq) is an excellent textbook for a course "Multidimentional Analysis".
All methods are presented very clearly and in detail manner. Very good exapmles are the most valuable parts of all chapters. Multivariate Applications in Substance Use Research: New Methods for New Questions 1st Edition.
Edited By Jennifer S. Rose, Laurie Chassin, Clark C. Presson, Steven J. Sherman J This edited volume introduces the latest advances in quantitative methods and illustrates ways to apply these methods to important questions in substance use research.
Now in its 6 th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6 th edition retains many key.
Agresti, in International Encyclopedia of the Social & Behavioral Sciences, This article deals with discrete multivariate analysis of categorical response variables. A categorical variable is one for which the measurement scale is a set of categories.
For studies having two or more categorical variables, a contingency table displays the counts for their cross-classification of categories.
Longitudinal Data Analysis: A Practical Guide for Researchers in Aging, Health, and Social Sciences (Multivariate Applications Series Book 18) - Kindle edition by Newsom, Jason, Jones, Richard N., Hofer, Scott M. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Longitudinal Data Analysis: A.
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Book Longitudinal Data Analysis: A Practical Guide for Researchers in Aging, Health, and Social Sciences - Multivariate Applications Series, which can be read online, published by the company: Taylor & Francis Ltd.
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Multivariate Analysis for the Biobehavioral and Social Sciences: A Graphical Approach outlines the essential multivariate methods for understanding data in the social and biobehavioral sciences. Using real-world data and the latest software applications, the book addresses the topic in a comprehensible and hands-on manner, making complex.
Today multivariate statistics and mathematical modeling procedures are applied regularly to problems arising in the physical sciences, biological sciences, social sciences, and humanities. This chapter introduces five topics in roughly the order users encounter them in the data analysis process.
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Multivariate analysis is what people called many machine learning techniques before calling it machine learning became so lucrative. Traditional multivariate analysis emphasizes theory concerning the multivariate normal distribution, techniques based on the multivariate normal distribution, and techniques that don't require a distributional assumption, but had better work well for.
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Beginning with an overview of the univariate general linear model, this volume defines the key steps in analyzing linear model data and introduces multivariate linear model analysis as a generalization.