Applied Univariate, Bivariate, and Multivariate Statistics. Daniel J. Denis
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APPLIED UNIVARIATE, BIVARIATE, AND MULTIVARIATE STATISTICS: UNDERSTANDING STATISTICS FOR SOCIAL AND NATURAL SCIENTISTS, WITH APPLICATIONS IN SPSS AND R
Second Edition
DANIEL J. DENIS
This second edition first published 2021
© 2021 John Wiley & Sons, Inc.
Edition History John Wiley and Sons, Inc. (1e. 2016)
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To Kaiser
PREFACE
Technology is not progress. Empathy is. The dogs are watching us.
Now in its second edition, this book provides a general introduction and overview of univariate through to multivariate statistical modeling techniques typically used in the social, behavioral, and related sciences. Students reading this book will come from a variety of fields, including psychology, sociology, education, political science, biology, medicine, economics, business, forestry, nursing, chemistry, law, among others. The book should be of interest to anyone who desires a relatively compact and succinct survey and overview of statistical techniques useful for analyzing data in these fields, while also wanting to understand and appreciate some of the theory behind these tools. Spanning several statistical methods, the focus of the book is naturally one of breadth than of depth into any one particular technique, focusing on the unifying principles as well as what substantively (scientifically) can or cannot be concluded from a method when applied to real data. These are topics usually encountered by upper division undergraduate or beginning graduate students in the aforementioned fields.
The first edition has also been used widely as a reference resource for both students and researchers working on dissertations, manuscripts, and other publications. It is hoped to provide the student with a “big picture” overview of how applied statistical modeling works, while at the same time providing him or her the opportunity in many places to implement, to some extent at least, many of these models using SPSS and/or R software. References and recommendations for further reading are provided throughout the text for readers who wish to pursue these topics further. Each topic and software demonstration can literally be “unpacked” into a deeper discussion, and so long as the reader is aware of this, they will appreciate this book for what it is—a bird's eye view of applied statistics, and not the “one and only” source they should refer to when conducting analyses. The book does not pretend to be a complete compendium of each statistical method it discusses, but rather is a survey of each method in hopes of conveying how these methods generally “work,” what technical elements unites virtually all of them, and the benefits and limitations of how they may be used in addressing scientific questions.
This second edition has been revised to make the book clearer and more accessible compared to the first edition. The book also contains a gentle introduction (“foot in the door”) to a variety of new topics that did not appear in the first edition. All chapters have been edited to varying degrees to improve clarity of prose and in places provide more information or clarification of the concept under discussion. The following is a summary of updates and revisions in the second edition:
Significant revision and corrections of errata appearing in the first edition. The second edition is a stronger and better book because it has been thoroughly re‐read and edited in places where rewording was required. In this sense, the second edition has undergone very much “vetting” since the first edition. At the same time, some sections have been entirely deleted from the first edition due to their explanations being too brief to make them worthwhile. These are sections that did not seem to “work” in the first edition,