Essentials of Multivariate Data Analysis

Neil H. Spencer

ISBN 10: 1466584785 / ISBN 13: 9781466584785

Published by Chapman And Hall/CRC, 2014

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Accessible to students and researchers without a substantial background in statistics or mathematics, this text explains the usefulness of multivariate methods in applied research. Unlike most books on multivariate methods, this one makes straightforward analyses easy to perform for those who are unfamiliar with advanced mathematical formulae. It uses an easily understood dataset to help explain the techniques and an Excel add-in to enable basic analyses, with both available on the book's CRC Press web page.

Seller Inventory # 9781466584785

Bibliographic Details

• Title: Essentials of Multivariate Data Analysis
• Publisher: Chapman And Hall/CRC
• Publication Date: 2014
• Language: English
• ISBN 10: 1466584785
• ISBN 13: 9781466584785
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 216W x 140H x 10D millimeters 216 millimeters width by 140 millimeters height by 10 millimeters depth
• Weight: 245 grams

About this title

Synopsis

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 most books on multivariate methods, this one makes straightforward analyses easy to perform for those who are unfamiliar with advanced mathematical formulae. An easily understood dataset is used throughout to illustrate the techniques. The accompanying add-in for Microsoft Excel® can be used to carry out the analyses in the text. The dataset and Excel add-in are available for download on the book’s CRC Press web page.

Providing a firm foundation in the most commonly used multivariate techniques, this text helps readers choose the appropriate method, learn how to apply it, and understand how to interpret the results. It prepares them for more complex analyses using software such as Minitab®, R, SAS, SPSS, and Stata.

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.