Lingua: Inglese
Editore: CreateSpace Independent Publishing Platform, 2015
ISBN 10: 1456538837 ISBN 13: 9781456538835
Da: Goodwill of Silicon Valley, SAN JOSE, CA, U.S.A.
Condizione: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear.
Lingua: Inglese
Editore: CreateSpace Independent Publishing Platform, 2015
ISBN 10: 1456538837 ISBN 13: 9781456538835
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 51,46
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: Createspace Independent Publishing Platform, 2015
ISBN 10: 1456538837 ISBN 13: 9781456538835
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 35,36
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Lingua: Inglese
Editore: Createspace Independent Publishing Platform, 2015
ISBN 10: 1456538837 ISBN 13: 9781456538835
Da: CitiRetail, Stevenage, Regno Unito
EUR 40,96
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. Multivariate Statistics: Old School is a mathematical and methodological introduction to multivariate statistical analysis. It presents the basic mathematical grounding that graduate statistics students need for future research, and important multivariate techniques useful to statisticians in general. The material provides support for further study in big data and machine learning. Topics include The multivariate normal and Wishart distributions Linear models, including multivariate regression and analysis of variance, and both-sides models (GMANOVA, repeated measures, growth curves) Linear algebra useful for multivariate statistics Covariance structures, including principal components, factor analysis, independence and conditional independence, and symmetry models Classification (linear and quadratic discrimination, trees, logistic regression) Clustering (K-means, model-based, hierarchical) Other techniques, including biplots, canonical correlations, and multidimensional scaling Most of the analyses in the book use the statistical computing environment R, for which there is an available package (msos) of multivariate routines and data sets. This text was developed over many years by the author, John Marden, while teaching in the Department of Statistics, University of Illinois at Urbana-Champaign. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.