Its conceptual non-mathematical approach is especially helpful to students, researchers, and managers in the social and health sciences, education, and business. It is also the ideal springboard for those who will pursue advanced study of these powerful multivariate techniques.
"synopsis" may belong to another edition of this title.
This book is intended as an introduction to multivariate statistical analysis for individuals with a minimal mathematics background.
The presentation is conceptual in nature with emphasis on the rationales, applications, and interpretations of the most commonly used multivariate techniques, rather than on their mathematical, computational, and theoretical aspects. As such, the book is intended primarily not for the I reader in 100 who will go on to specialize in statistical analysis, but for the other 99 who will only obtain an overview of the subject, yet will have to deal in their professional lives with the design, analysis, and interpretation of research by interfacing with specialists in the field.
Although a prior course in elementary statistics would be beneficial, it is not absolutely essential, since the fundamentals are thoroughly reviewed in the first two chapters. Consequently, the book can be used either as an introductory or intermediate level text, and will also find use as a reference volume for those already in the professional community.
Since the principles of statistical analysis are perfectly general, cutting across all academic disciplines, students in all curriculums can use the text. This is especially true since much of the book is devoted to the discussion of concepts and principles rather than to specific examples. The illustrations that are used are drawn from three major areas-monetary disciplines, including business, economics, and government; behavioral disciplines, including education, psychology, sociology, anthropology, political science, and communications; and organic disciplines, including biology, medicine, and agriculture. Students of the physical sciences and engineering are advised to take a mathematical statistics course where they can capitalize on their backgrounds in calculus and matrix algebra, although such students can also benefit from the present approach.
I am grateful to the Literary Executor of the late Sir Ronald A. Fisher, F.R.S., to Dr. Frank Yates, F.R.S. and to Longman Group Ltd. .London, for permission to use Tables II, III, and IV from their book Statistical Tables for Biological, Agricultural and Medical Research (6th edition, 1974). I am also thankful to the dozens of individuals who made helpful comments at various stages of the manuscript. While many of the suggestions were heeded, I accept responsibility for any shortcomings that remain.
S.K.K. New York, New York October, 1981
Preface to the Second Edition
Aside from some minor textual changes, the main difference of this book from the initial 1982 edition is the addition of a chapter on Multidimensional Scaling. This chapter is taken from my 1986 textbook "Statistical Analysis: An Interdisciplinary Introduction to Univariate and Multivariate Methods," which is a more full-scale text, containing all the material in this edition plus a more thorough coverage of univariate, experimental design, multiple comparisons, time series, and probability topics, as well as providing student exercises.
Another new feature of this edition is its availability as an economical paperback. For many instructors the 1986 Statistical Analysis text - which is twice the length of this book - is too comprehensive for their particular curriculum needs, despite their desire to cover multivariate methods in an introductory manner. Consequently, this paperback edition will afford instructors greater flexibility in the design of their courses.
Not only will this edition serve as a basic introductory course in multivariate methods for the many students who do not have extensive mathematical backgrounds, but it will also complement those multivariate texts which are often too technical to fully benefit all the students enrolled in such courses.
Moreover, the conceptual approach of this book should prove to be a valuable guide for both graduate and undergraduate introductory courses, providing an integrated overview of the most useful analytical techniques that students are bound to encounter in their future studies and research activities.
S.K.K. New York, New York April, 1991
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