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For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable int...
|a Applied multivariate statistical analysis /
|c Richard Johnson, Dean Wichern.
250
|a 6th ed.
260
|a Edinburgh Gate :
|b Pearson,
|c 2014
300
|a 770 p.
505
0
|a 1. Aspects of multivariate analysis -- 2. Sample geometry and random sampling -- 3. Matrix algebra and random vectors -- 4. The multivariate normal distribution -- 5. Inferences about a mean vector -- 6. Comparisons of several multivariate means -- 7. Multivariate linear regressions models -- 8. Principal components -- 9. Factor analysis and inference for structured covariance matrices -- 10. Canonical correlation analysis -- 11. Discrimination and classification -- 12. Clustering, distance methods and ordination -- Appendix.
520
3
|a For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.
