The present volume is devoted to the study of language use in translated texts as a function of various linguistic, contextual and cognitive factors. It contributes to the recent trend in empirical translation studies towards more methodological sophistication, including mixed methodology designs and multivariate statistical analyses, ultimately leading to a more accurate understanding of language use in translations.
Concepts of positive dependence are becoming increasingly important in probability, statistics and their applications. While these concepts are traditionally viewed as focusing on positive and negative dependence for random vectors, they also are related to broader issues in the modeling and the analysis of multivariate data, and, in particular, ordinal data. Historically, positive dependence for the multivariate normal distribution had been synonymous with positive correlations. Other subsequently developed multivariate distributions were often interpreted with this perspective.
Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, Second Edition (Multivariate Applications Series)
Added by: mortezaactive2 | Karma: 28.55 | Black Hole | 9 January 2015
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Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, Second Edition (Multivariate Applications Series)
This bestselling text provides a practical guide to the basic concepts of structural equation modeling (SEM) and the AMOS program (Versions 17 & 18). The author reviews SEM applications based on actual data taken from her research. Noted for its non-mathematical language, this book is written for
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For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. Hair, et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques.
