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An Introduction to Probability and Statistical Inference 25 May 2013 George G. Roussas, "An Introduction to Probability and Statistical Inference"2003 | ISBN-10: 0125990200 | 523 pages | PDF | 3,2 MB Probability models, statistical methods, and the information to be gained from them is vital for work in business, engineering, sciences (including social and behavioral), and other fields. Data must be properly collected, analyzed an Abstract Inference (Probability & Mathematical Statistics) 30 September 2011 Abstract Inference Probability & Mathematical Statistics 1981 | 538 | ISBN: 0471082678 | DJVU | 3 Mb The title of this book is ambiguous, and intentionally so. On the one hand, Abstract Inference can refer to problems of statistical inference when the sample space is an abstract space. On the other, it can refer to the case when the parameter space is an abstract space. ... Linear Statistical Inference and its Applications, 2nd edition 13 April 2015 Linear Statistical Inference and its Applications, 2nd editionby C. Radhakrishna Rao English | 2001 | ISBN: 0471218758 | 656 pages | DJVU | 4.56 MB Statistical Inference: A Short Course 28 June 2013 Statistical Inference: A Short Courseby Michael J. Panik 2012 | ISBN: 1118229401 | English | 400 Pages | PDF | 3.45 MB Probability & Statistics Engineers 8th Edition 7 November 2010 Probability & Statistics Engineers 8th EditionEnglish | 2009 | 285 pages | PDF | 56 MB With its unique balance of theory and methodology, this classic text provides a rigorous introduction to basic probability theory and statistical inference, motivated by interesting, relevant applications. Offers extensively updated coverage, new problem sets, and chapter-ending material to enhance the book's relevance to today's engineers and scientists. Statistical Inference Based on Divergence Measures 24 November 2010 Statistical Inference Based on Divergence Measures 2006 | 512 | ISBN: 1584886005 | PDF | 3 Mb The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this powerful approach.... GARCH Models: Structure, Statistical Inference and Financial Applications 20 January 2011 GARCH Models: Structure, Statistical Inference and Financial Applications by Christian Francq, Jean-Michel Zakoian
Publisher: WILEY | 2010 | ISBN 0470683910 | PDF | 504 pages | 12 MBApplied Statistical Inference with MINITAB 23 September 2014 Sally Lesik, "Applied Statistical Inference with MINITAB"English | ISBN: 1420065831 | 2010 | 464 pages | PDF | 15 MB Statistical Inference for Models with Multivariate t-Distributed Errors 10 October 2014 Statistical Inference for Models with Multivariate t-Distributed ErrorsEnglish | 2014 | ISBN: 1118854055 | 272 pages | PDF | 7,8 MB This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors: Introduction to Probability and Statistics 14th Edition 21 February 2013 Introduction to Probability and Statistics 14th EditionEnglish | ISBN: 1133103758 | edition 2012 | PDF | 744 pages | 45.6 MB Used by hundreds of thousands of students, INTRODUCTION TO PROBABILITY AND STATISTICS, Fourteenth Edition, blends proven coverage with new innovations to ensure you gain a solid understanding of statistical concepts--and see their relevance to your everyday life. The new edition retains the text's straightforward presentation and traditional outline for descriptive and inferential statistics while incorporating modern technology--including computational software and interactive visual tools--to help you master statistical reasoning and skillfully interpret statistical results. Drawing from decades of classroom teaching experience, the authors clearly illustrate how to apply statistical procedures as they explain how to describe real sets of data, what statistical tests mean in terms of practical application, how to evaluate the validity of the assumptions behind statistical tests, and what to do when statistical assumptions have been violated. Statistics can be an intimidating course, but with this text you will be well prepared. With its thorough explanations, insightful examples, practical exercises, and innovative technology features, this text equips you with a firm foundation in statistical concepts, as well as the tools to apply them to the world around you. |