Applied multivariate statistics for the
โ James P. Stevens
๐ Library
๐
2001
๐ Psychology Press
๐ English
โฆ LIBER โฆ
๐
Applied multivariate statistics for the social sciences
โ Scribed by James P. Stevens
- Publisher
- Psychology Press
- Year
- 2001
- Tongue
- English
- Leaves
- 708
- Series
- Applied Multivariate STATS
- Edition
- 4
- Category
- Library
โฌ Acquire This Volume
No coin nor oath required. For personal study only.
โฆ Synopsis
This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size (by providing guidelines) so that the results can be generalized. The new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.<br
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<P>Now in its 6<SUP>th</SUP> edition, the authoritative textbook <I>Applied Multivariate Statistics for the Social Sciences</I>, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies.
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2015
๐ Routledge
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<P>Now in its 6<SUP>th</SUP> edition, the authoritative textbook <I>Applied Multivariate Statistics for the Social Sciences</I>, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies.