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Multivariate Statistical Analysis

A Conceptual Introduction, 2nd Edition

Ocena książki

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  • 303 strony
  • 11 godzin czytania

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This classic multivariate statistics book has become the introduction of choice for researchers and students with a minimal mathematics background. In addition to providing a review of fundamental statistical methods, it provides a basic treatment of advanced computer-based multivariate analytical techniques; including correlation and regression analysis, analysis of variance, discriminant analysis, factor analysis, cluster analysis, and multidimensional scaling. The conceptual treatment emphasizes the rationales, applications, and interpretations, rather than the theoretical mathematical aspects of the most commonly used data analysis techniques in use today, closing the gap between spiraling technology and its intelligent application, providing students and researchers with a decided advantage in their future studies and careers. Its conceptual non-mathematical approach is especially helpful to students, researchers, and managers in the social and health sciences, education, and business. It is also the ideal springboard for those who will pursue advanced study of these powerful multivariate techniques.

Zakup książki

Multivariate Statistical Analysis, Sam Kash Kachigan

Język
Rok wydania
1991
Oprawa
(miękka)
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4,2
Bardzo dobra
46 Ocena

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Tytuł
Multivariate Statistical Analysis
Podtytuł
A Conceptual Introduction, 2nd Edition
Język
angielski
Rok wydania
1991
Oprawa
miękka
Liczba stron
303
ISBN10
0942154916
ISBN13
9780942154917
Seria
Tagi
Nauka
Ocena
4,15 z 5
Opis
This classic multivariate statistics book has become the introduction of choice for researchers and students with a minimal mathematics background. In addition to providing a review of fundamental statistical methods, it provides a basic treatment of advanced computer-based multivariate analytical techniques; including correlation and regression analysis, analysis of variance, discriminant analysis, factor analysis, cluster analysis, and multidimensional scaling. The conceptual treatment emphasizes the rationales, applications, and interpretations, rather than the theoretical mathematical aspects of the most commonly used data analysis techniques in use today, closing the gap between spiraling technology and its intelligent application, providing students and researchers with a decided advantage in their future studies and careers. Its conceptual non-mathematical approach is especially helpful to students, researchers, and managers in the social and health sciences, education, and business. It is also the ideal springboard for those who will pursue advanced study of these powerful multivariate techniques.