Editing Multivariate statistics (section)

==History==
[[C.R. Rao]] made significant contributions to multivariate statistical theory throughout his career, particularly in the mid-20th century. One of his key works is the book titled "Advanced Statistical Methods in Biometric Research," published in 1952. This work laid the foundation for many concepts in multivariate statistics.<ref>{{cite journal | doi=10.1073/pnas.2321318121 | title=C.R. Rao: Paramount statistical scientist (1920 to 2023) | date=2024 | last1=Dasgupta | first1=Anirban | journal=Proceedings of the National Academy of Sciences | volume=121 | issue=9 | pages=e2321318121 | pmid=38377193 | pmc=10907269 | bibcode=2024PNAS..12121318D }}</ref>
Anderson's 1958 textbook,'' An Introduction to Multivariate Statistical Analysis'',<ref>[[Theodore Wilbur Anderson|T.W. Anderson]] (1958) '' An Introduction to Multivariate Analysis'', New York: Wiley {{ISBN|0471026409}}; 2e (1984) {{ISBN|0471889873}}; 3e (2003) {{ISBN|0471360910}}</ref> educated a generation of theorists and applied  statisticians; Anderson's book emphasizes [[hypothesis testing]] via [[likelihood ratio test]]s and the properties of [[Statistical power|power function]]s: [[admissible decision rule|admissibility]], [[bias of an estimator|unbiasedness]] and [[monotonicity]].<ref>{{cite journal|doi =10.2307/2289251|title =Review: Contemporary Textbooks on Multivariate Statistical Analysis: A Panoramic Appraisal and Critique|first9 =K. V.|last10 =Kent|first10 =J. T.|last11 =Bibby|first11 =J. M.|last12 =Morrison|first12 =D. F.|last13 =Muirhead|first13 =R. J.|last14 =Press|first14 =S. J.|last15 =Rao|first15 =C. R.|last16 =Roy|first16 =S. N.|last17 =Gnanadesikan|first17 =R.|last18 =Srivastava|first18 =J. N.|last19 =Seber|first19 =G. A. F.|last20 =Srivastava|first20 =M. S.|last21 =Khatri|first21 =C. G.|last22 =Takeuchi|first22 =K.|last23 =Yanai|first23 =H.|last24 =Mukherjee|first24 =B. N.|last9 =Mardia|first8 =A. M.|last8 =Kshirsagar|first7 =M. G.|last7 =Kendall|first6 =R.|last6 =Gnanadesikan|first5 =N. C.|last5 =Giri|first4 =M. L.|last4 =Eaton|first3 =S. F.|last3 =Arnold|first2 =T. W.|last2 =Anderson|last1=Sen|first1=Pranab Kumar|author1-link=Pranab K. Sen|journal=[[Journal of the American Statistical Association]]| volume=81 | issue=394 |date=June 1986|pages=560–564| jstor=2289251 | issn=0162-1459 |display-authors =8}}(Pages 560–561)</ref><ref>{{cite journal|doi =10.1214/ss/1177013111|title =A Review of Multivariate Analysis|last=Schervish|first=Mark J.| journal=Statistical Science| volume=2|issue=4|date=November 1987|pages=396–413|jstor=2245530|issn =0883-4237|doi-access=free}}
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MVA was formerly discussed solely in the context of statistical theories, due to the size and complexity of underlying datasets and its high computational consumption. With the dramatic growth of computational power, MVA now plays an increasingly important role in data analysis and has wide application in [[Omics]] fields.