Applied Multivariate Statistics for the Social Sciences
โ Scribed by James P. Stevens
- Publisher
- Lawrence Erlbaum Associates
- Year
- 2002
- Tongue
- English
- Leaves
- 708
- Series
- Applied Multivariate STATS
- Edition
- 4th ed
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
A textbook for courses on advanced statistical methods or multivariate statistics for students in the social sciences with little or no training in multivariate methods. Previous study is required in the factorial analysis of variance, but not in matrix algebra. No dates are noted for previous editions. The ISBN on the back cover is different.
๐ SIMILAR VOLUMES
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
Routledge, 2009. โ 664 p. โ 5th ed. โ ISBN: 0805859012, 9780805859010<div class="bb-sep"></div>This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narra
This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a re
<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.
<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.