Traditional statistical inference is integrated with the more modern idea of data analysis in this introductory text for non-technical students. Material begins with simple data sets and proceeds to those with more structure. Examples are plentiful and have been chosen from diverse fields, making the subject accessible to students of any academic field. The book contains many pictures as well as detailed calculations with step-by-step instructions and a formula to indicate in mathematical notation exactly what is being done. At the end of each chapter is a brief summary which reviews the material and explains key terms. Following this are questions which help readers review main new concepts and ideas, and practice problems (many with real data sets). This text requires limited background in mathematics.
"synopsis" may belong to another edition of this title.
A straightforward book that integrates the traditional foundations of statistical inference with the more modern ideas of data analysis. Divided into three sections, it begins with a description of data in general and groups of numbers in particular. Part two develops concepts of randomness, probability and statistical inference. Lastly, it applies these ideas to more complex data structures and the analysis of relationships. This edition contains more problems, exercises and updated examples. Computer output is systematically included throughout the text.
Andrew F. Siegel holds the Grant I. Butterbaugh Professorship in Quantitative Methods and Finance at the Michael G. Foster School of Business, University of Washington, Seattle, and is also Adjunct Professor in the Department of Statistics. His Ph.D. is in statistics from Stanford University (1977). Before settling in Seattle, he held teaching and/ or research positions at Harvard University, the University of Wisconsin, the RAND Corporation, the Smithsonian Institution, and Princeton University. He has taught statistics at both undergraduate and graduate levels, and earned seven teaching awards in 2015 and 2016. The interest-rate model he developed with Charles Nelson (the Nelson-Siegel Model) is in use at central banks around the world. His work has been translated into Chinese and Russian. His articles have appeared in many publications, including the Journal of the American Statistical Association, the Encyclopedia of Statistical Sciences, the American Statistician, Proceedings of the National Academy of Sciences, Nature, the American Mathematical Monthly, the Journal of the Royal Statistical Society, the Annals of Statistics, the Annals of Probability, the Society for Industrial and Applied Mathematics Journal on Scientific and Statistical Computing, Statistics in Medicine, Biometrika, Biometrics, Statistical Applications in Genetics and Molecular Biology, Mathematical Finance, Contemporary Accounting Research, the Journal of Finance, and the Journal of Applied Probability.
"About this title" may belong to another edition of this title.
Shipping:
US$ 15.40
From United Kingdom to U.S.A.
Seller: Anybook.com, Lincoln, United Kingdom
Condition: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Book contains highlighter markings. With owner's inscription inside cover. In poor condition, suitable as a reading copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,950grams, ISBN:047189186X. Seller Inventory # 9145258
Quantity: 1 available
Seller: Anybook.com, Lincoln, United Kingdom
Condition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,950grams, ISBN:047189186X. Seller Inventory # 9919421
Quantity: 1 available