Probability and Statistical Inference Pearson New International Edition

Author: Robert V. Hogg
Publisher:
ISBN: 129202478X
Release Date: 2013-07-23
Genre: Mathematical statistics

Written by two leading statisticians, this applied introduction to the mathematics of probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.

Probability and Statistical Inference Global Edition

Author: Robert V. Hogg
Publisher: Pearson Higher Ed
ISBN: 9781292062563
Release Date: 2015-02-27
Genre: Mathematics

For a one- or two-semester course; calculus background presumed, no previous study of probability or statistics is required. Written by three veteran statisticians, this applied introduction to probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.

Probability and Statistics for Engineers and Scientists

Author: Ronald E. Walpole
Publisher:
ISBN: 0130984698
Release Date: 2002
Genre: Engineering

For undergraduates studying engineering, science or computer science. This classic text provides a rigorous introduction to basic probability theory and statistical inference motivated by applications. Assumes a background in calculus; offers a unique balance of theory and methodology.

Probability Statistics for Engineers Scientists MyStatLab Global Edition

Author: Ronald E. Walpole
Publisher: Pearson Higher Ed
ISBN: 9781292161419
Release Date: 2016-08-15
Genre: Mathematics

For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance between theory and methodology. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. This revision focuses on improved clarity and deeper understanding. This latest edition is also available in as an enhanced Pearson eText. This exciting new version features an embedded version of StatCrunch, allowing students to analyze data sets while reading the book. MyStatLab™ is not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. MyStatLab is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts.

Probability and Statistics

Author: Morris H. DeGroot
Publisher: Pearson College Division
ISBN: 0321500466
Release Date: 2012
Genre: Mathematics

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.

Statistical Inference

Author: George Casella
Publisher: Duxbury Resource Center
ISBN: 0495391875
Release Date: 2008
Genre: Inferenzstatistik

This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be used for students majoring in statistics who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

Probability and Statistical Inference

Author: Nitis Mukhopadhyay
Publisher: CRC Press
ISBN: 0824703790
Release Date: 2000-03-22
Genre: Mathematics

Priced very competitively compared with other textbooks at this level! This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts. Beginning with an introduction to the basic ideas and techniques in probability theory and progressing to more rigorous topics, Probability and Statistical Inference studies the Helmert transformation for normal distributions and the waiting time between failures for exponential distributions develops notions of convergence in probability and distribution spotlights the central limit theorem (CLT) for the sample variance introduces sampling distributions and the Cornish-Fisher expansions concentrates on the fundamentals of sufficiency, information, completeness, and ancillarity explains Basu's Theorem as well as location, scale, and location-scale families of distributions covers moment estimators, maximum likelihood estimators (MLE), Rao-Blackwellization, and the Cramér-Rao inequality discusses uniformly minimum variance unbiased estimators (UMVUE) and Lehmann-Scheffé Theorems focuses on the Neyman-Pearson theory of most powerful (MP) and uniformly most powerful (UMP) tests of hypotheses, as well as confidence intervals includes the likelihood ratio (LR) tests for the mean, variance, and correlation coefficient summarizes Bayesian methods describes the monotone likelihood ratio (MLR) property handles variance stabilizing transformations provides a historical context for statistics and statistical discoveries showcases great statisticians through biographical notes Employing over 1400 equations to reinforce its subject matter, Probability and Statistical Inference is a groundbreaking text for first-year graduate and upper-level undergraduate courses in probability and statistical inference who have completed a calculus prerequisite, as well as a supplemental text for classes in Advanced Statistical Inference or Decision Theory.

Mathematical Statistics

Author: Peter J. Bickel
Publisher: CRC Press
ISBN: 9781498722704
Release Date: 2015-11-04
Genre: Business & Economics

Mathematical Statistics: Basic Ideas and Selected Topics, Volume II presents important statistical concepts, methods, and tools not covered in the authors’ previous volume. This second volume focuses on inference in non- and semiparametric models. It not only reexamines the procedures introduced in the first volume from a more sophisticated point of view but also addresses new problems originating from the analysis of estimation of functions and other complex decision procedures and large-scale data analysis. The book covers asymptotic efficiency in semiparametric models from the Le Cam and Fisherian points of view as well as some finite sample size optimality criteria based on Lehmann–Scheffé theory. It develops the theory of semiparametric maximum likelihood estimation with applications to areas such as survival analysis. It also discusses methods of inference based on sieve models and asymptotic testing theory. The remainder of the book is devoted to model and variable selection, Monte Carlo methods, nonparametric curve estimation, and prediction, classification, and machine learning topics. The necessary background material is included in an appendix. Using the tools and methods developed in this textbook, students will be ready for advanced research in modern statistics. Numerous examples illustrate statistical modeling and inference concepts while end-of-chapter problems reinforce elementary concepts and introduce important new topics. As in Volume I, measure theory is not required for understanding. Check out Volume I for fundamental, classical statistical concepts leading to the material in this volume.

Miller Freund s Probability and Statistics for Engineers

Author: Richard Johnson
Publisher: Pearson
ISBN: 9780134194806
Release Date: 2016-01-28
Genre: Mathematics

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For an introductory, one or two semester, or sophomore-junior level course in Probability and Statistics or Applied Statistics for engineering, physical science, and mathematics students. An Applications-Focused Introduction to Probability and Statistics Miller & Freund's Probability and Statistics for Engineers is rich in exercises and examples, and explores both elementary probability and basic statistics, with an emphasis on engineering and science applications. Much of the data has been collected from the author's own consulting experience and from discussions with scientists and engineers about the use of statistics in their fields. In later chapters, the text emphasizes designed experiments, especially two-level factorial design. The Ninth Edition includes several new datasets and examples showing application of statistics in scientific investigations, familiarizing students with the latest methods, and readying them to become real-world engineers and scientists.

An Introduction to Probability and Statistics

Author: Vijay K. Rohatgi
Publisher: John Wiley & Sons
ISBN: 9781118799659
Release Date: 2015-09-01
Genre: Mathematics

A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability. The second part addresses statistical inference, and the remainingchapters focus on special topics. An Introduction to Probability and Statistics, Third Edition includes: A new section on regression analysis to include multiple regression, logistic regression, and Poisson regression A reorganized chapter on large sample theory to emphasize the growing role of asymptotic statistics Additional topical coverage on bootstrapping, estimation procedures, and resampling Discussions on invariance, ancillary statistics, conjugate prior distributions, and invariant confidence intervals Over 550 problems and answers to most problems, as well as 350 worked out examples and 200 remarks Numerous figures to further illustrate examples and proofs throughout An Introduction to Probability and Statistics, Third Edition is an ideal reference and resource for scientists and engineers in the fields of statistics, mathematics, physics, industrial management, and engineering. The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics.

Probability and Statistics Pearson New International Edition

Author: Morris H. DeGroot
Publisher: Pearson Higher Ed
ISBN: 9781292037677
Release Date: 2013-08-29
Genre: Mathematics

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Probability & Statistics, Fourth Edition, was written for a one- or two-semester probability and statistics course. This course is offered primarily at four-year institutions and taken mostly by sophomore and junior level students majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.

Essentials of Probability Statistics for Engineers Scientists Pearson New International Edition

Author: Ronald E. Walpole
Publisher: Pearson Higher Ed
ISBN: 9781292035734
Release Date: 2013-08-28
Genre:

For junior/senior undergraduates taking a one-semester probability and statistics course as applied to engineering, science, or computer science. This text covers the essential topics needed for a fundamental understanding of basic statistics and its applications in the fields of engineering and the sciences. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. Students using this text should have the equivalent of the completion of one semester of differential and integral calculus.

John E Freund s Mathematical Statistics with Applications

Author: Irwin Miller
Publisher: Pearson
ISBN: 9780134291673
Release Date: 2015-12-03
Genre: Mathematics

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. John E. Freund's Mathematical Statistics with Applications , Eighth Edition, provides a calculus-based introduction to the theory and application of statistics, based on comprehensive coverage that reflects the latest in statistical thinking, the teaching of statistics, and current practices.

Applied Multivariate Statistical Analysis Pearson New International Edition

Author: Richard A. Johnson
Publisher: Pearson Higher Ed
ISBN: 9781292037578
Release Date: 2013-08-29
Genre: Psychology

For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.