Analyzing and Modeling Rank Data
Book Details
Format
Hardback or Cased Book
ISBN-10
0412995212
ISBN-13
9780412995217
Publisher
Taylor & Francis Ltd
Imprint
Chapman & Hall/CRC
Country of Manufacture
US
Country of Publication
GB
Publication Date
Aug 1st, 1996
Print length
344 Pages
Weight
638 grams
Dimensions
21.50 x 14.90 x 2.40 cms
Product Classification:
Probability & statisticsMathematical modelling
AI Summary
Ksh 30,600.00
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This book is the first single source volume to fully address this prevalent practice in both its analytical and modeling aspects
This book is the first single source volume to fully address this prevalent practice in both its analytical and modeling aspects. The information discussed presents the use of data consisting of rankings in such diverse fields as psychology, animal science, educational testing, sociology, economics, and biology. This book systematically presents the basic models and methods for analyzing data in the form of ranks. Integrating material from a wide range of fields, this book applies graphical, numerical, and modeling techniques to data sets, uncovering fascinating structures in the rank data.
Providing the most extensive coverage of the subject found in statistical literature, this book will be a welcomed reference to statisticians. In addition, this volume is also accessible to people in all areas of quantitative research. Researchers in psychology and consumer preference will discover a valuable resource; and sociologists, biologists, political and animal scientists will also benefit. As a text, it will be ideal for graduate students in courses on statistics and other quantitative disciplines.
Providing the most extensive coverage of the subject found in statistical literature, this book will be a welcomed reference to statisticians. In addition, this volume is also accessible to people in all areas of quantitative research. Researchers in psychology and consumer preference will discover a valuable resource; and sociologists, biologists, political and animal scientists will also benefit. As a text, it will be ideal for graduate students in courses on statistics and other quantitative disciplines.
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