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Methods of Multivariate Analysis
Abstract
Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."-IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life sit
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Citations
Cited by
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Regression analysis for prediction of residential energy consumption
Fumo, N., & Rafe Biswas, M. A. (2015) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.03.035 · Cited by 630
Adams, D. C. (2014) · Evolution · doi:10.1111/evo.12463 · Cited by 286
Pataky, T. C., Vanrenterghem, J., & Robinson, M. A. (2016) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2016.03.032 · Cited by 187
A meta-analysis of empirical e-government research and its future research implications
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Metadata
- Authors
- Rencher, A. C., & Christensen, W. F.
- Venue
- Wiley Series in Probability and Statistics
- Publisher
- Wiley
- Published
- 2012-07-16
- ISSN
- 1940-6347 (ISSN-L)
- OpenAlex
- W2498923140
- Cited by
- 763
- References
- 0
- FWCI
- 6.82
- Type
- book
- Language
- en
- Open access
- closed
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- Rencher, A. C., & Christensen, W. F. (2012). Methods of Multivariate Analysis. Wiley Series in Probability and Statistics. https://doi.org/10.1002/9781118391686
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
