Essentials of Multivariate Data Analysis
Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike m
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Essentials of Multivariate Data Analysis
Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike m
74.99 In Stock
Essentials of Multivariate Data Analysis

Essentials of Multivariate Data Analysis

by Neil H. Spencer
Essentials of Multivariate Data Analysis

Essentials of Multivariate Data Analysis

by Neil H. Spencer

eBook

$74.99 

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Overview

Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike m

Product Details

ISBN-13: 9781040176955
Publisher: CRC Press
Publication date: 12/17/2013
Sold by: Barnes & Noble
Format: eBook
Pages: 186
File size: 3 MB

About the Author

Dr. Neil H. Spencer is a reader in applied statistics and director of the Statistical Services and Consultancy Unit at the University of Hertfordshire. His research interests include multilevel models, multivariate methods, statistical computing, multiple testing, and testing for randomness.

Table of Contents

Frequently Asked Questions. Graphical Presentation of Multivariate Data. Multivariate Tests of Significance. Factor Analysis. Cluster Analysis. Discriminant Analysis. Multidimensional Scaling. Correspondence Analysis. References. Index.
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