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Journal articles on the topic 'Multivariate statistical analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Mathew, Thomas. "Multivariate Statistical Analysis." Technometrics 39, no. 1 (1997): 101. http://dx.doi.org/10.1080/00401706.1997.10485445.

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2

Trenkler, Götz. "Multivariate statistical analysis." Computational Statistics & Data Analysis 24, no. 3 (1997): 372. http://dx.doi.org/10.1016/s0167-9473(97)87027-2.

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3

Copeland, Karen A. F. "Multivariate Statistical Analysis." Journal of Quality Technology 29, no. 4 (1997): 494. http://dx.doi.org/10.1080/00224065.1997.11979809.

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4

Haigh, John, R. A. Johnson, and D. W. Wichern. "Applied Multivariate Statistical Analysis." Mathematical Gazette 72, no. 462 (1988): 331. http://dx.doi.org/10.2307/3619964.

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5

Ziegel, Eric R., Richard A. Johnson, and Dean W. Wichern. "Applied Multivariate Statistical Analysis." Technometrics 41, no. 1 (1999): 81. http://dx.doi.org/10.2307/1271011.

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6

Lachenbruch, P. A., L. Lebart, A. Morineau, and K. M. Warwick. "Multivariate Descriptive Statistical Analysis." Biometrics 41, no. 2 (1985): 592. http://dx.doi.org/10.2307/2530887.

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7

Johnson, A. R., and D. W. Wichern. "Applied Multivariate Statistical Analysis." Biometrics 44, no. 3 (1988): 920. http://dx.doi.org/10.2307/2531616.

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8

Johnson, R. A., and D. W. Wichern. "Applied Multivariate Statistical Analysis." Biometrics 54, no. 3 (1998): 1203. http://dx.doi.org/10.2307/2533879.

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9

Heckler, Charles E. "Applied Multivariate Statistical Analysis." Technometrics 47, no. 4 (2005): 517. http://dx.doi.org/10.1198/tech.2005.s319.

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10

Dunn, Charles. "Applied Multivariate Statistical Analysis." Technometrics 31, no. 2 (1989): 265–66. http://dx.doi.org/10.1080/00401706.1989.10488530.

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11

Cliff, Andrew D., Daniel A. Griffith, and Carl G. Amrhein. "Multivariate Statistical Analysis for Geographers." Journal of the American Statistical Association 94, no. 446 (1999): 654. http://dx.doi.org/10.2307/2670195.

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12

Rowe, D. B., and R. G. Hoffmann. "Multivariate statistical analysis in fMRI." IEEE Engineering in Medicine and Biology Magazine 25, no. 2 (2006): 60–64. http://dx.doi.org/10.1109/memb.2006.1607670.

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13

Greenhouse, Samuel W., and Heinz Kres. "Statistical Tables for Multivariate Analysis." Journal of the American Statistical Association 80, no. 391 (1985): 780. http://dx.doi.org/10.2307/2288513.

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14

Tucker, Raymond K. "Multivariate Statistical Models: II. The Multivariate Analysis of Variance." Perceptual and Motor Skills 69, no. 2 (1989): 562. http://dx.doi.org/10.2466/pms.1989.69.2.562.

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15

Muirhead, Robb J., and T. W. Anderson. "An Introduction to Multivariate Statistical Analysis." Journal of Business & Economic Statistics 4, no. 1 (1986): 135. http://dx.doi.org/10.2307/1391399.

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16

Verducci, Joseph S., H. Bozdogan, and A. K. Gupta. "Multivariate Statistical Modeling and Data Analysis." Journal of the American Statistical Association 84, no. 407 (1989): 847. http://dx.doi.org/10.2307/2289697.

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17

Tyurin, Yu N. "Multivariate Statistical Analysis: The Geometric Theory." Theory of Probability & Its Applications 55, no. 1 (2011): 91–109. http://dx.doi.org/10.1137/s0040585x97984620.

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18

Bicciato, Silvo, Andrea Bagno, Marco Soldà, Riccardo Manfredini, and Carlo Di Bello. "Fermentation Diagnosis by Multivariate Statistical Analysis." Applied Biochemistry and Biotechnology 102-103, no. 1-6 (2002): 049–62. http://dx.doi.org/10.1385/abab:102-103:1-6:049.

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19

Pirhadi, Somayeh, Fereshteh Shiri, and Jahan B. Ghasemi. "Multivariate statistical analysis methods in QSAR." RSC Advances 5, no. 127 (2015): 104635–65. http://dx.doi.org/10.1039/c5ra10729f.

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20

Schmee, Josef. "An Introduction to Multivariate Statistical Analysis." Technometrics 28, no. 2 (1986): 180–81. http://dx.doi.org/10.1080/00401706.1986.10488123.

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21

Ziegel, Eric. "Multivariate Statistical Modelling and Data Analysis." Technometrics 31, no. 3 (1989): 393. http://dx.doi.org/10.1080/00401706.1989.10488579.

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22

O'Connor, C. "An introduction to multivariate statistical analysis." Computers & Mathematics with Applications 14, no. 9-12 (1987): 951. http://dx.doi.org/10.1016/0898-1221(87)90246-x.

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23

Serdobol'skii, V. I. "Theory of essentially multivariate statistical analysis." Russian Mathematical Surveys 54, no. 2 (1999): 351–79. http://dx.doi.org/10.1070/rm1999v054n02abeh000133.

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24

Bozdogan, H., and A. K. Gupta. "Multivariate Statistical Modeling and Data Analysis." Applied Statistics 38, no. 3 (1989): 522. http://dx.doi.org/10.2307/2347741.

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25

Skinner, C. J., and T. W. Anderson. "An Introduction to Multivariate Statistical Analysis." Journal of the Royal Statistical Society. Series A (General) 148, no. 2 (1985): 164. http://dx.doi.org/10.2307/2981950.

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26

Boys, Richard J., H. Bozdogan, and A. K. Gupta. "Multivariate Statistical Modeling and Data Analysis." Journal of the Royal Statistical Society. Series A (Statistics in Society) 151, no. 3 (1988): 548. http://dx.doi.org/10.2307/2983004.

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27

Fujikoshi, Yasunori. "Siotani's Contributions to Multivariate Statistical Analysis." American Journal of Mathematical and Management Sciences 15, no. 3-4 (1995): 199–214. http://dx.doi.org/10.1080/01966324.1995.10737397.

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28

Novák, J., H. Sůvová, and J. Vondráček. "Multivariate statistical methods as a tool of financial analysis of farm businesses." Agricultural Economics (Zemědělská ekonomika) 48, No. 1 (2012): 9–12. http://dx.doi.org/10.17221/5281-agricecon.

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The paper is focused on the evaluation of the possibilities of analysing the relations between economic and financial indicators of farm businesses by the application of multivariate statistical methods. It also indicates the possibilities of the construction of a general economic indicator of business effectiveness.

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29

Nesrine, Nasri, Bouhlila Rachida, and Riadh Ahmed. "Multivariate Statistical Analysis of Saline Water — A Case Study: Sabkha Oum LeKhialate (Tunisia)." International Journal of Environmental Science and Development 6, no. 1 (2015): 40–43. http://dx.doi.org/10.7763/ijesd.2015.v6.558.

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30

McManus, Catherine E., Nancy J. McMillan, James Dowe, and Julie Bell. "Diamonds Certify Themselves: Multivariate Statistical Provenance Analysis." Minerals 10, no. 10 (2020): 916. http://dx.doi.org/10.3390/min10100916.

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The country or mine of origin is an important economic and societal issue inherent in the diamond industry. Consumers increasingly want to know the provenance of their diamonds to ensure their purchase does not support inhumane working conditions. Governments around the world reduce the flow of conflict diamonds via paper certificates through the Kimberley Process, a United Nations mandate. However, certificates can be subject to fraud and do not provide a failsafe solution to stopping the flow of illicit diamonds. A solution tied to the diamonds themselves that can withstand the cutting and m

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31

AKBULUT, Omer, and Canturk CAPIK. "Multivariate Statistical Analysis and Required Sample Size." Journal of Nursology 25, no. 2 (2022): 111–16. http://dx.doi.org/10.5152/janhs.2022.970637.

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32

Shitikov, V. K., and T. D. Zinchenko. "Multivariate statistical analysis of ecological communities (review)." Theoretical and Applied Ecology, no. 1 (2019): 5–11. http://dx.doi.org/10.25750/1995-4301-2019-1-005-011.

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33

Lozano-Perez, S. "Improving EFTEM data using multivariate statistical analysis." Journal of Physics: Conference Series 126 (August 1, 2008): 012040. http://dx.doi.org/10.1088/1742-6596/126/1/012040.

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34

Pollock, D. S. G. "An index notation for multivariate statistical analysis." International Journal of Mathematical Education in Science and Technology 22, no. 4 (1991): 657–67. http://dx.doi.org/10.1080/0020739910220417.

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35

Kosaki, Takashi, Kikuo Wasano, and Anthony S. R. Juo. "Multivariate statistical analysis of yield-determining factors." Soil Science and Plant Nutrition 35, no. 4 (1989): 597–607. http://dx.doi.org/10.1080/00380768.1989.10434795.

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36

Grunsky, E. C. "Aspects of multivariate statistical analysis in geology." Computers & Geosciences 27, no. 2 (2001): 255–56. http://dx.doi.org/10.1016/s0098-3004(00)00094-7.

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37

Kotula, P. G., and M. H. Van Benthem. "Revisiting Noise Scaling for Multivariate Statistical Analysis." Microscopy and Microanalysis 21, S3 (2015): 1423–24. http://dx.doi.org/10.1017/s1431927615007898.

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38

Fontanazza, C. M., V. Notaro, V. Puleo, and G. Freni. "Multivariate Statistical Analysis for Water Demand Modeling." Procedia Engineering 89 (2014): 901–8. http://dx.doi.org/10.1016/j.proeng.2014.11.523.

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39

Keenan, Michael R., and Paul G. Kotula. "Multivariate Statistical Analysis of EEL-Spectral Images." Microscopy and Microanalysis 10, S02 (2004): 874–75. http://dx.doi.org/10.1017/s1431927604880620.

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40

dos Santos, Fabíola Menezes, Denise de La Corte Bacci, Antonio Roberto Saad, and Anderson Targino da Silva Ferreira. "Geodiversity index weighted by multivariate statistical analysis." Applied Geomatics 12, no. 3 (2020): 361–70. http://dx.doi.org/10.1007/s12518-020-00303-w.

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41

Andreu, Manuel J., Jose C. Dávila, M. Angeles Real, and Salvador Guirado. "Multivariate statistical analysis of golgi stained neurons." Neuroscience Research 24, no. 3 (1996): 215–26. http://dx.doi.org/10.1016/0168-0102(95)00997-3.

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42

Stanimirova, I., S. Tsakovski, and V. Simeonov. "Multivariate statistical analysis of coastal sediment data." Fresenius' Journal of Analytical Chemistry 365, no. 6 (1999): 489–93. http://dx.doi.org/10.1007/s002160051510.

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43

Ross, D. Lauren. "Multivariate Statistical Analysis of Environmental Monitoring Data." Ground Water 35, no. 6 (1997): 1050–57. http://dx.doi.org/10.1111/j.1745-6584.1997.tb00177.x.

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44

Tong, Y. L. "Some Majorization Inequalities in Multivariate Statistical Analysis." SIAM Review 30, no. 4 (1988): 602–22. http://dx.doi.org/10.1137/1030135.

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45

Hempkins, W. B., R. H. Kingsborough, W. E. Lohec, and C. J. Nini. "Multivariate Statistical Analysis of Stuck Drillpipe Situations." SPE Drilling Engineering 2, no. 03 (1987): 237–44. http://dx.doi.org/10.2118/14181-pa.

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46

Jankovic, Slobodan. "The Multivariate Statistical Analysis – Multiple Linear Regression." International Journal on Biomedicine and Healthcare 10, no. 4 (2022): 173. http://dx.doi.org/10.5455/ijbh.2022.10.173-175.

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Background. When processing the results of observational studies we ave to usemultivariate statistical methods that will examine the simultaneous influence of both independent and confounding variables on the outcome, Objective: The aim of this paper is to further explain how a researcher could decide whether multiple linear regression is suitable statistical option for processing his (her) data, and then how to implement it properly. Methods: This article is a narrative review of literature about logic, assumptions, quality check and interpretation of multiple linear regression. Results: Mult

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47

Santos, João Pedro, Christian Crémona, André D. Orcesi, and Paulo Silveira. "Multivariate statistical analysis for early damage detection." Engineering Structures 56 (November 2013): 273–85. http://dx.doi.org/10.1016/j.engstruct.2013.05.022.

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48

Bonnet, N., and P. Hannequin. "Chemical mapping and Multivariate Statistical Analysis (prospect)." Ultramicroscopy 28, no. 1-4 (1989): 248–51. http://dx.doi.org/10.1016/0304-3991(89)90303-3.

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49

Rios, Ferdinand G., John I. Thornton, and Kevin S. Guarino. "Multivariate statistical analysis of shotgun pellet dispersion." Forensic Science International 32, no. 1 (1986): 21–28. http://dx.doi.org/10.1016/0379-0738(86)90154-4.

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50

Simeonov, Vasil, Juergen Einax, Stafan Tsakovski, and Joerg Kraft. "Multivariate statistical assessment of polluted soils." Open Chemistry 3, no. 1 (2005): 1–9. http://dx.doi.org/10.2478/bf02476233.

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AbstractThis study deals with the application of several multivariate statistical methods (cluster analysis, principal components analysis, multiple regression on absolute principal components scores) for assessment of soil pollution by heavy metals. The sampling was performed in a heavily polluted region and the chemometric analysis revealed four latent factors, which describe 84.5 % of the total variance of the system, responsible for the data structure. These factors, whose identity was proved also by cluster analysis, were conditionally named “ore specific”, “metal industrial”, “cement ind

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