Introductory Statistical Inference
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Introductory Statistical Inference
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Author : Nitis Mukhopadhyay
language : en
Publisher: CRC Press
Release Date : 2006-02-07
Introductory Statistical Inference written by Nitis Mukhopadhyay and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-07 with Mathematics categories.
Introductory Statistical Inference develops the concepts and intricacies of statistical inference. With a review of probability concepts, this book discusses topics such as sufficiency, ancillarity, point estimation, minimum variance estimation, confidence intervals, multiple comparisons, and large-sample inference. It introduces techniques of two-stage sampling, fitting a straight line to data, tests of hypotheses, nonparametric methods, and the bootstrap method. It also features worked examples of statistical principles as well as exercises with hints. This text is suited for courses in probability and statistical inference at the upper-level undergraduate and graduate levels.
Introductory Statistical Inference With The Likelihood Function
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Author : Charles A. Rohde
language : en
Publisher:
Release Date : 2014-11-30
Introductory Statistical Inference With The Likelihood Function written by Charles A. Rohde and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-30 with categories.
Introductory Statistical Inference With The Likelihood Function
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Author : Charles A. Rohde
language : en
Publisher: Springer
Release Date : 2014-10-31
Introductory Statistical Inference With The Likelihood Function written by Charles A. Rohde and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-31 with Medical categories.
This textbook covers the fundamentals of statistical inference and statistical theory including Bayesian and frequentist approaches and methodology possible without excessive emphasis on the underlying mathematics. This book is about some of the basic principles of statistics that are necessary to understand and evaluate methods for analyzing complex data sets. The likelihood function is used for pure likelihood inference throughout the book. There is also coverage of severity and finite population sampling. The material was developed from an introductory statistical theory course taught by the author at the Johns Hopkins University’s Department of Biostatistics. Students and instructors in public health programs will benefit from the likelihood modeling approach that is used throughout the text. This will also appeal to epidemiologists and psychometricians. After a brief introduction, there are chapters on estimation, hypothesis testing, and maximum likelihood modeling. The book concludes with sections on Bayesian computation and inference. An appendix contains unique coverage of the interpretation of probability, and coverage of probability and mathematical concepts.
Solutions Manual Introductory Statistical Inference
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Author : Nitis Mukhopadhyay
language : en
Publisher: CRC PressI Llc
Release Date : 2006-02-01
Solutions Manual Introductory Statistical Inference written by Nitis Mukhopadhyay and has been published by CRC PressI Llc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-01 with Mathematics categories.
Introduction To Statistical Inference
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Author : E. S. Keeping
language : en
Publisher: Courier Corporation
Release Date : 1995-01-01
Introduction To Statistical Inference written by E. S. Keeping and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-01-01 with Mathematics categories.
This excellent text emphasizes the inferential and decision-making aspects of statistics. The first chapter is mainly concerned with the elements of the calculus of probability. Additional chapters cover the general properties of distributions, testing hypotheses, and more.
Introduction To Linear Models And Statistical Inference
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Author : Steven J. Janke
language : en
Publisher: John Wiley & Sons
Release Date : 2005-09-15
Introduction To Linear Models And Statistical Inference written by Steven J. Janke and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-09-15 with Mathematics categories.
A multidisciplinary approach that emphasizes learning by analyzing real-world data sets This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. These examples are developed and analyzed throughout the text, and more complicated examples of data sets are introduced along the way. Taking a multidisciplinary approach, the book traces the conclusion of the analyses of data sets taken from geology, biology, economics, psychology, education, sociology, and environmental science. As students learn to analyze the data sets, they master increasingly sophisticated linear modeling techniques, including: * Simple linear models * Multivariate models * Model building * Analysis of variance (ANOVA) * Analysis of covariance (ANCOVA) * Logistic regression * Total least squares The basics of statistical analysis are developed and emphasized, particularly in testing the assumptions and drawing inferences from linear models. Exercises are included at the end of each chapter to test students' skills before moving on to more advanced techniques and models. These exercises are marked to indicate whether calculus, linear algebra, or computer skills are needed. Unlike other texts in the field, the mathematics underlying the models is carefully explained and accessible to students who may not have any background in calculus or linear algebra. Most chapters include an optional final section on linear algebra for students interested in developing a deeper understanding. The many data sets that appear in the text are available on the book's Web site. The MINITAB(r) software program is used to illustrate many of the examples. For students unfamiliar with MINITAB(r), an appendix introduces the key features needed to study linear models. With its multidisciplinary approach and use of real-world data sets that bring the subject alive, this is an excellent introduction to linear models for students in any of the natural or social sciences.
Solutions Manual For Introductory Statistical Inference
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Author : Mukhopadhyay/Nitis
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2006-03-01
Solutions Manual For Introductory Statistical Inference written by Mukhopadhyay/Nitis and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-01 with categories.
Introductory Statistics
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Author : J. Gosling
language : en
Publisher: Pascal Press
Release Date : 1995
Introductory Statistics written by J. Gosling and has been published by Pascal Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Juvenile Nonfiction categories.
A comprehensive, self-paced, step-by-step statistics course for tertiary students.
Introduction To The Theory Of Statistical Inference
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Author : Hannelore Liero
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Introduction To The Theory Of Statistical Inference written by Hannelore Liero and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Mathematics categories.
Based on the authors' lecture notes, this text presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Unlike related textbooks, it combines the theoretical basis of statistical inference with a useful applied toolbox that includes linear models. Suitable for a second semester undergraduate course on statistical inference, the text offers proofs to support the mathematics and does not require any use of measure theory. It illustrates core concepts using cartoons and provides solutions to all examples and problems.
Introduction To Statistical Inference
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Author : Jack C. Kiefer
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Introduction To Statistical Inference written by Jack C. Kiefer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This book is based upon lecture notes developed by Jack Kiefer for a course in statistical inference he taught at Cornell University. The notes were distributed to the class in lieu of a textbook, and the problems were used for homework assignments. Relying only on modest prerequisites of probability theory and cal culus, Kiefer's approach to a first course in statistics is to present the central ideas of the modem mathematical theory with a minimum of fuss and formality. He is able to do this by using a rich mixture of examples, pictures, and math ematical derivations to complement a clear and logical discussion of the important ideas in plain English. The straightforwardness of Kiefer's presentation is remarkable in view of the sophistication and depth of his examination of the major theme: How should an intelligent person formulate a statistical problem and choose a statistical procedure to apply to it? Kiefer's view, in the same spirit as Neyman and Wald, is that one should try to assess the consequences of a statistical choice in some quan titative (frequentist) formulation and ought to choose a course of action that is verifiably optimal (or nearly so) without regard to the perceived "attractiveness" of certain dogmas and methods.