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Topic: Multivariate statistics

Related Topics

MANOVA

Canonical correlation analysis

List of publications in statistics

Wishart distribution

Statistical phenomena

Multivariate normal distribution

Statistics

Principal components analysis

Analysis of variance

Applied statistics

Monte Carlo methods in finance

Multivariate gamma function

Regression analysis

Logistic regression

Bayesian inference

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	APA Books (Site not responding. Last check: 2007-10-21)
		The most commonly used multivariate techniques are examined in detail: multiple regression and correlation, path analysis, principal-components analysis, exploratory and confirmatory factor analysis, multidimensional scaling, analysis of cross-classified data, logistic regression, multivariate analysis of variance (MANOVA), discriminant analysis, and meta-analysis.
		Statistical notations are explained, underlying assumptions are described, and terms are defined clearly and understandably.
		Multivariate Statistics is an ideal companion to any multivariate research text for performing these analyses, so in addition to research consumers it will be helpful to students and investigators learning to use a particular analysis for the first time.
	www.apa.org /books/4316510.html (309 words)

	Multivariate statistics - Wikipedia, the free encyclopedia
		Multivariate statistics or multivariate statistical analysis in statistics describes a collection of procedures which involve observation and analysis of more than one statistical variable at a time.
		Logistic regression allows to perform a regression analysis to estimate and test the influence of covariates on a binary response.
		Multivariate analysis of variance (MANOVA) methods extend analysis of variance methods to cover cases where there is more than one dependent variable and where the dependent variables cannot simply be combined.
	en.wikipedia.org /wiki/Multivariate_statistics (240 words)

	Multivariate Statistics
		Course Description: EXST 7037, Comparison of multivariate techniques and analyses; emphasis on discriminant analysis, factor analysis and principal component analysis, canonical correlation, cluster analysis, and multivariate analysis of variance and repeated measures.
		Help student to recognize multivariate data and situations when multivariate analysis is necessary or may prove beneficial.
		Provide hands-on practice with multivariate techniques that are often employed in the preparation of theses, dissertations, and research papers.
	www.stat.lsu.edu /faculty/moser/exst7037/syll7037-2004.html (353 words)

	Annotated Bibliography of Articles for the Statistics User
		This paper is a Monte Carlo study of the relative advantages of using a univariate or a multivariate approach to repeated measures data.
		Multivariate methods will be more powerful when the number of subjects is greater than the number of levels by a few.
		There will be a large difference in power between the univariate and multivariate method when small but reliable effects are present with effects highly variable but averaging to zero over subjects, in which case the multivariate test will be more powerful.
	www.math.yorku.ca /SCS/biblio.html (4852 words)

	Multivariate Statistics for Wildlife and Ecology Research
		With its focus on the practical application of the techniques of multivariate statistics, this book shapes the powerful tools of statistics for the specific needs of ecologists and makes statistics more applicable to their course of study.
		Multivariate Statistics for Wildlife and Ecology Research gives the reader a solid conceptual understanding of the role of multivariate statistics in ecological applications and the relationships among various techniques, while avoiding detailed mathematics and underlying theory.
		Whether used as a textbook for specialized courses or as a supplement to general statistics texts, the book emphasizes those techniques that students of ecology and natural resources most need to understand and employ in their research.
	www.umass.edu /landeco/pubs/statsbook.html (451 words)

	Powell's Books - Theory of Multivariate Statistics (Springer Texts in Statistics) by Martin Bilodeau (Site not responding. Last check: 2007-10-21)
		All of Statistics: A Concise Course in Statistical Inference
		Martin Bilodeau is Professor in the Department of Mathematics and Statistics at the Université de Montréal.
		David Brenner is Professor of Statistics in the Department of Statistics at the University of Toronto with over 20 years experience as an educator.
	www.powells.com /biblio?isbn=0387987398 (484 words)

	Book: The Geometry of Multivariate Statistics (Site not responding. Last check: 2007-10-21)
		A traditional approach to developing multivariate statistical theory is algebraic.
		This book is designed to help the reader develop a way of thinking about multivariate statistics, as well as to understand in a broader and more intuitive sense what the procedures do and how their results are interpreted.
		Presenting important procedures of multivariate statistical theory geometrically, the author hopes that this emphasis on the geometry will give the reader a coherent picture into which all the multivariate techniques fit.
	www.assess.com /Books/b-16569.htm (251 words)

	StatManual: A Manual for Univariate & Multivariate Statistics
		Therefore, designs which utilize multiple independent variables can be and are included in the univariate section of statistical techniques.
		Multivariate methods provide an optimal linear combination of dependent variables that satisfy specific statistical criteria.
		These procedures include: (a) multivariate analogues of correlation and prediction techniques, (b) multivariate analogues of ANOVA significance tests, and (c) the classification of individuals into categories on the basis of predictor information.
	www.uwsp.edu /psych/cw/statmanual (99 words)

	statistics
		Adventures in Statistics We describe a mathematics project involving fifth grade students and the area of classrooms, which incorporates measurement, graphing, computation, data analysis, and presentation of results.
		Java Applets for Visualisation of Statistical Concepts from VESTAC - "These applets are designed for the purpose of computer-aided education in statistic courses.
		It is an introductory course in statistics that is designed to provide you with the basic concepts and methods of statistical analysis for decision making under uncertainties.
	www.emtech.net /statistics.htm (1510 words)

	Amazon.com: Books: Reading and Understanding Multivariate Statistics (Site not responding. Last check: 2007-10-21)
		As someone who has tried to teach multivariate statistics to non-statistician graduate students for the past 5 years, I have found this to be a very valuable and clearly-written text.
		As advertised and as the previous reviewer noted, the text is largely free of complex statistical equations and instead has clear descriptions of each type of test as well as common applications of that test.
		It is a perfect introduction for students who are intimidated by numbers and equations yet need to know about multivariate statistics for their graduate studies.
	www.amazon.com /exec/obidos/tg/detail/-/1557982732?v=glance (1257 words)

	Book: Reading and Understanding More Multivariate Statistics (Site not responding. Last check: 2007-10-21)
		In Reading and Understanding MORE Multivariate Statistics, the editors have responded to reader requests to provide the same accessible approach to a new group of multivariate techniques and related topics in measurement.
		As with the previous volume, chapter authors describe the research questions for which the statistic is most appropriate, the underlying assumptions and rationale of the analysis, and the logic behind interpreting the results.
		Whether you are a graduate student, researcher, or consumer of research, this volume is guaranteed to increase your comfort level and confidence in reading and understanding multivariate statistics.
	www.assess.com /Books/b-6983.htm (229 words)

	Statistics on the Web
		If you know of (or maintain) a statistics resource on the Web that you don't see here, please drop me a line to let me know about it, and I'll take a look at it.
		Contains info on how statistics are used in daily life, providing lots of examples suitable for use in teaching of statistics.
		This is a fantastic resource which gives guidelines for various types of statistical analysis, as well as a basic glossary.
	www.execpc.com /~helberg/statistics.html (4923 words)

	A few links related to Statistics Education
		Statistics Instruction Using Technology Target Audience: This software was developed for Educational Psychology 101, Analysis and Integration of Statistical Data in Education, an introductory statistics course for health, psychology, and education students.
		Statistical considerations for clinical trials and scientific experiments Find sample size, power or the minimal detectable difference for parallel studies, crossover studies, or studies to find associations between variables, where the dependent variable is Success or Failure, a Quantitative Measurement.
		Statistical Datasets The purpose of this electronic service is to provide access to a variety of datasets suitable for teaching statistics.
	noppa5.pc.helsinki.fi /links.html (9056 words)

	Multivariate Statistics: Introduction (Site not responding. Last check: 2007-10-21)
		Welcome to this introduction to the family of data analysis techniques often grouped together under the name, "multivariate statistics." The word multivariate should say it all -- these techniques look at the pattern of relationships between several variables simultaneously.
		We will look at three types of multivariate methods -- factor analysis, multidimensional scaling, and cluster analysis.
		Multivariate statistics help the researcher to summarize data and reduce the number of variables necessary to describe it.
	www.socialresearchmethods.net /tutorial/flynn/multivar.htm (619 words)

	Statistics and Statistical Graphics Resources
		Statistical Society of Canada Maintains a page of links to statistics pages, conferences, statistical organizations, government agencies, Canadian university statistics departments, and Case Studies to be explored at annual meetings.
		Studying statistics (advice) This page is aimed at undergraduates studying statistics for the first time.
		Discusses a new approach to the introductory statistics course based on the concepts of entities, properties of entities, and relationships between properties of entities.
	www.math.yorku.ca /SCS/StatResource.html (7408 words)

	Citations: Graphical Models in Applied Multivariate Statistics - Whittaker (ResearchIndex) (Site not responding. Last check: 2007-10-21)
		It is possible to perform statistical tests to check whether any given conditional independence is a reasonable hypothesis about the data.
		Then, the relevance measure value for each feature Y i, i = 1; n, is calculated as the average likelihood ratio test statistic for excluding an edge between Y i and any other feature in a graphical Gaussian model [38] This means that those features likely to remain conditional....
		Statistical image segmentation using Triplet Markov fields - Pieczynski, Benboudjema,..
	citeseer.ist.psu.edu /context/5497/0 (1892 words)

	Multivariate statistics
		-a specific statistical hypothesis, formulated in terms of the parameters of the multivariate populations, are tests (includes several mulitivariate methods)
		Matrix algebra is not difficult, but some fundamental exposure to it is required to understand how multivariate analyses are conducted.
		Don't use multivariate approaches if samples or EU's are difficult to obtain (or may die, missing observations typically result in loss of all data for that subject).
	www.usd.edu /~kolmstea/biostats/multivariate1.htm (571 words)

	Amazon.com: Books: Using Multivariate Statistics (4th Edition) (Site not responding. Last check: 2007-10-21)
		Given the increasingly user-friendly statistical software on the market, this book offers a quick antidote for the rising number of button pushers, by showing budding statisticians the implications of using a technique ignorantly.
		Although some of the information on statistical packages may now be a little dated, the program inputs and outputs are supplied, as are written-up reports of the results, similar to how they would appear in a socio-behavioral journal.
		This is the 'statistical bible' for graduate students or professors performing multivariate statistics in their research.
	www.amazon.com /exec/obidos/tg/detail/-/0321056779?v=glance (1737 words)

	Multivariate Statistics (PSY 320) (Weinfurt)
		There are usually multiple ways to explain a statistical issue, and sometimes you just need to hear it a different way.
		Each chapter is devoted to a different multivariate technique, with the goal of providing a conceptual understanding.
		This is a handy little book that suggests how to present results from statistical analyses in table form according to APA style.
	www.dcri.duke.edu /ccge/weinfurt/psy320/texts.html (596 words)

	multivariate statistics - ResearchIndex document query (Site not responding. Last check: 2007-10-21)
		This paper presents a novel method using a multivariate statistical framework for producing a model of the
		and it is of fundamental importance in multivariate statistical analysis.
		are analyzed by the usual methods of multivariate statistics.
	citeseer.ist.psu.edu /cs?qb=dbnum%3D1%2Cstart%3D20%2Cao%3DCitations%2Cam%3D20%2Caf%3DAny%2Cqtype%3Ddocument:&q=multivariate%20statistics (456 words)

	HyperStat Online: An Introductory Statistics Textbook and Online Tutorial for Help in Statistics Courses
		Statistics for journalists by Robert Niles of the LA Times.
		Multivariate statistics: Concepts, models, and applications by David W. Stockburger of Southwest Missouri State University
		Statistics 30X class notes by H. Newton, J. Carroll, N. Wang, and D. Whiting of Texas AandM.
	davidmlane.com /hyperstat/index.html (568 words)

	Using Multivariate Statistics, 4/E - Allyn & Bacon / Longman Catalog
		This text takes a practical approach to multivariate data analysis, with an introduction to the most commonly encountered statistical and multivariate techniques.
		Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses.
		Overall, it provides advanced students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics.
	www.ablongman.com /catalog/academic/product/0,4096,0321056779,00.html (171 words)

	Multivariate Analyses
		Multivariate Analysis, K. Mardia, J. Kent, and J. Bibby.
		The book contains the basic linear algebra, nuts and bolts of several important multivariate statistical methods, ways to interpret the resutls, examples with real numbers, and intermediate calculations that are often omitted in other textbooks.
		It is used by Dr. Boik for a gradulate level multivariate statistics class in the statistics department.)
	www.esg.montana.edu /eguchi/multivariate (489 words)

	Book: A Primer of Multivariate Statistics (Third Edition) (Site not responding. Last check: 2007-10-21)
		Drawing upon over 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why.
		Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.
		"The coverage of the book is essentially classical multivariate statistics, based on the normal distribution, plus a discussion of factor analysis.
	www.assess.com /Books/b-32106.htm (302 words)

	Multivariate Methods - Blaine
		Multivariate forms of multiple linear regression, analysis of variance and analysis of co-variance.
		Statistical methods in psychology journals: Guidelines and explanations.
		Psychology 7291: Multivariate Statistics (Gregory Carey, University of Colorado, Boulder)
	www2.hawaii.edu /~daniel/614.html (1139 words)

	Statistics 501 - Multivariate Statistical Methods
		Inferential methods based on the assumption of multivariate normally distributed population will be discussed.
		Graphics will be heavily utilized in all topics.
		Schedule of topics: Introduction Graphics Multivariate Normal Inference for the population mean Handling Missing Values Comparing several population means Principal Component Analysis Supervised Classification Unsupervised Classification Factor Analysis Multidimensional scaling Canonical Correlation Course Goals: The objectives of the course are to help students: 1.
	www.public.iastate.edu /~dicook/stat501.html (332 words)

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