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Introductory Statistical Inference - Mukhopadhyay, Nitis
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ISBN: 9781574446135

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Probability and Distributions Introduction About Sets Axiomatic Development of Probability Conditional Probability and Independent Events Discrete Random Variables Continuous Random Variables Some Useful Distributions Exercises and Complements Moments and Generating Functions Introduction Expectation and Variance Moments and Moment Generating Function Determination of a Distribution via MGF Probability Generating Function Exercises and Complements Multivariate Random Variables Introduction Probability Distributions Covariances and Correlation Coefficient Independence of Random Variables Bivariate Normal Distribution Correlation Coefficient and Independence Exponential Family Selected Probability Inequalities Exercises and Complements Sampling Distribution Introduction Moment Generating Function Approach Order Statistics Transformation Special Sampling Distributions Multivariate Normal Distribution Selected Reviews in Matrices Exercises and Complements Notions of Convergence Introduction Convergence in Probability Convergence in Distribution Convergence of Chi-Square, t, and F distributions Exercises and Complements Sufficiency, Completeness, and Ancillarity Introduction Sufficiency Minimal Sufficiency Information Ancillarity Completeness Exercises and Complements Point Estimation Introduction Maximum Likelihood Estimator Criteria to Compare Estimators Improved Unbiased Estimators via Sufficiency Uniformly Minimum Variance Unbiased Estimator Consistent Estimator Exercises and Complements Tests of Hypotheses Introduction Error Probabilities and Power Function Simple Null vs. Simple Alternative One-Sided Composite Alternative Simple Null vs. Two-Sided Alternative Exercises and Complements Confidence Intervals Introduction One-Sample Problems Two-Sample Problems Exercises and Complements Bayesian Methods Introduction Prior and Posterior Distributions Conjugate Prior Point Estimation Examples with a Nonconjugate Prior Exercises and Complements Likelihood Ratio and Other Tests Introduction One-Sample LR Tests: Normal Two-Sample LR Tests: Independent Normal Bivariate Normal Exercises and Complements Large-Sample Methods Introduction Maximum Likelihood Estimation Asymptotic Relative Efficiency Confidence Intervals and Tests of Hypotheses Variance Stabilizing Transformation Exercises and Complements Abbreviations, Historical Notes, and Tables Abbreviations and Notations Historical Notes Selected Statistical Tables References Answers: Selected Exercises Author Index Subject Index Mathematics Mathematics eBook, CRC Press

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Introductory Stat Inference
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ISBN: 9781574446135

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This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques. Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques. Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of distributions, and standard probability inequalities. It develops the Helmert transformation for normal distributions, introduces the notions of convergence, and spotlights the central limit theorems. Coverage highlights sampling distributions, Basu's theorem, Rao-Blackwellization and the Cramér-Rao inequality. The text also provides in-depth coverage of Lehmann-Scheffé theorems, focuses on tests of hypotheses, describes Bayesian methods and the Bayes' estimator, and develops large-sample inference. The author provides a historical context for statistics and statistical discoveries and answers to a majority of the end-of-chapter exercises. Designed primarily for a one-semester, first-year graduate course in probability and statistical inference, this text serves readers from varied backgrounds, ranging from engineering, economics, agriculture, and bioscience to finance, financial mathematics, operations and information management, and psychology. Textbooks New, Books~~Mathematics~~Probability & Statistics~~General, Introductory-Stat-Inference~~Nitis-Mukhopadhyay, , , , , , , , , , Taylor & Francis

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Introductory Statistical Inference
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Introductory Statistical Inference - neues Buch

ISBN: 9781574446135

ID: 13588056

This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques. Beginning with a review of the basic concepts and methods in. This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques. Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of distributions, and standard probability inequalities. It develops the Helmert transformation for normal distributions, introduces the notions of convergence, and spotlights the central limit theorems. Coverage highlights sampling distributions, Basu's theorem, Rao-Blackwellization and the Cramer-Rao inequality. The text also provides in-depth coverage of Lehmann-Scheffe theorems, focuses on tests of hypotheses, describes Bayesian methods and the Bayes' estimator, and develops large-sample inference. The author provides a historical context for statistics and statistical discoveries and answers to a majority of the end-of-chapter exercises. Designed primarily for a one-semester, first-year graduate course in probability and statistical inference, this text serves readers from varied backgrounds, ranging from engineering, economics, agriculture, and bioscience to finance, financial mathematics, operations and information management, and psychology. Books, Science and Geography~~Mathematics~~Probability & Statistics, Introductory Statistical Inference~~Book~~9781574446135~~Nitis Mukhopadhya, , , , , , , , , ,

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Introductory Statistical Inference (Statistics, Textbooks and Monographs) - Nitis Mukhopadhyay, Mukhopadhyay Mukhopadhyay
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[SR: 2452814], Gebundene Ausgabe, [EAN: 9781574446135], St Lucie Pr, St Lucie Pr, Book, [PU: St Lucie Pr], St Lucie Pr, 56254011, Wahrscheinlichkeit & Statistik, 56248011, Angewandte Mathematik, 56214011, Mathematik, 56047011, Fachbücher, 54071011, Genres, 52044011, Fremdsprachige Bücher

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Introductory Statistical Inference (Statistics: A Series of Textbooks and Monographs) - Nitis Mukhopadhyay
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ISBN: 1574446134

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[EAN: 9781574446135], Neubuch, [PU: Chapman and Hall/CRC]

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Introductory Statistical Inference
Autor:

Mukhopadhyay, Nitis; Mukhopadhyay, Mukhopadhyay

Titel:

Introductory Statistical Inference

ISBN-Nummer:

1574446134

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.

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EAN (ISBN-13): 9781574446135
ISBN (ISBN-10): 1574446134
Gebundene Ausgabe
Erscheinungsjahr: 2006
Herausgeber: ST LUCIE PR
304 Seiten
Gewicht: 0,549 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 06.11.2007 21:37:08
Buch zuletzt gefunden am 22.07.2016 13:06:28
ISBN/EAN: 1574446134

ISBN - alternative Schreibweisen:
1-57444-613-4, 978-1-57444-613-5

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