Probability And Statistical Inference Download Ebook PDF Epub Online

Author : Nitis Mukhopadhyay
Publisher : CRC Press
Release : 2020-08-30
Page : 665
Category : Mathematics
ISBN 13 : 1000291553
Description :


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 wi


Author : J.G. Kalbfleisch
Publisher : Springer Science & Business Media
Release : 2012-12-06
Page :
Category : Mathematics
ISBN 13 : 1468400916
Description :



Author : Robert V. Hogg
Elliot A. Tanis
Publisher : Pearson College Division
Release : 2013
Page : 544
Category : Mathematics
ISBN 13 : 9780321923271
Description :


Normal 0 false false false 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.


Author : Robert V. Hogg
Elliot A. Tanis
Publisher : Macmillan College
Release : 1988
Page : 658
Category : Mathematical statistics
ISBN 13 :
Description :


This user-friendly introduction to the mathematics of probability and statistics (for readers with a background in calculus) uses numerous applications--drawn from biology, education, economics, engineering, environmental studies, exercise science, health science, manufacturing, opinion polls, psychology, sociology, and sports--to help explain and motivate the concepts. A review of selected mathematical techniques is included, and an accompanying CD-ROM contains many of the figures (many animated), and the data included in the examples and exercises (stored in both Minitab compatible format and ASCII). Empirical and Probability Distributions. Probability. Discrete Distributions. Continuous Distributions. Multivariable Distributions. Sampling Distribution Theory. Importance of Understanding Variability. Estimation. Tests of Statistical Hypotheses. Theory of Statistical Inference. Quality Improvement Through Statistical Methods. For anyone interested in the Mathematics of Probability and Statistics.


Author : Robert Bartoszynski
Magdalena Niewiadomska-Bugaj
Publisher : John Wiley & Sons
Release : 2020-12-22
Page : 592
Category : Mathematics
ISBN 13 : 1119243807
Description :


Updated classic statistics text, with new problems and examples Probability and Statistical Inference, Third Edition helps students grasp essential concepts of statistics and its probabilistic foundations. This book focuses on the development of intuition and understanding in the subject through a wealth of examples illustrating concepts, theorems, and methods. The reader will recognize and fully understand the why and not just the how behind the introduced material. In this Third Edition, the reader will find a new chapter on Bayesian statistics, 70 new problems and an appendix with the supporting R code. This book is suitable for upper-level undergraduates or first-year graduate students studying statistics or related disciplines, such as mathematics or engineering. This Third Edition: Introduces an all-new chapter on Bayesian statistics and offers thorough explanations of advanced statistics and probability topics Includes 650 problems and over 400 examples - an excellent resource for the mathematical statistics class sequence in the increasingly popular "flipped classroom" format Offers students in statistics, mathematics, engineering and related fields a user-friendly resource Provides practicing professionals valuable insight into statistical tools Probability and Statistical Inference offers a unique approach to problems that allows the reader to fully integrate the knowledge gained from the text, thus, enhancing a more complete and honest understanding of the topic.


Author : J.G. Kalbfleisch
Publisher : Springer
Release : 2012-09-27
Page : 343
Category : Mathematics
ISBN 13 : 9781461270096
Description :


A carefully written text, suitable as an introductory course for second or third year students. The main scope of the text guides students towards a critical understanding and handling of data sets together with the ensuing testing of hypotheses. This approach distinguishes it from many other texts using statistical decision theory as their underlying philosophy. This volume covers concepts from probability theory, backed by numerous problems with selected answers.


Author : Robert V. Hogg
Elliot A. Tanis
Publisher : Pearson
Release : 2019-01-11
Page : 560
Category :
ISBN 13 : 9780135189399
Description :


For one- or two-semester courses in Probability, Probability & Statistics, or Mathematical Statistics. An authoritative introduction to an in-demand field Advances in computing technology - particularly in science and business - have increased the need for more statistical scientists to examine the huge amount of data being collected. Written by veteran statisticians, Probability and Statistical Inference, 10th Edition emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. This applied introduction to probability and statistics reinforces basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts. It is designed for a two-semester course, but it can be adapted for a one-semester course. A good calculus background is needed, but no previous study of probability or statistics is required. 013518939X / 9780135189399 PROBABILITY AND STATISTICAL INFERENCE, 10/e


Author : James H. Stapleton
Publisher : John Wiley & Sons
Release : 2007-12-14
Page : 512
Category : Mathematics
ISBN 13 : 9780470183403
Description :


This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.


Author : Harold J. Larson
Publisher : Wiley
Release : 1982-05-05
Page : 656
Category : Mathematics
ISBN 13 :
Description :


Discusses probability theory and to many methods used in problems of statistical inference. The Third Edition features material on descriptive statistics. Cramer-Rao bounds for variance of estimators, two-sample inference procedures, bivariate normal probability law, F-Distribution, and the analysis of variance and non-parametric procedures. Contains numerous practical examples and exercises.


Author : George G. Roussas
Publisher : Academic Press
Release : 2014-10-21
Page : 624
Category : Mathematics
ISBN 13 : 0128004371
Description :


An Introduction to Probability and Statistical Inference, Second Edition, guides you through probability models and statistical methods and helps you to think critically about various concepts. Written by award-winning author George Roussas, this book introduces readers with no prior knowledge in probability or statistics to a thinking process to help them obtain the best solution to a posed question or situation. It provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations. This text contains an enhanced number of exercises and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities. Reorganized material is included in the statistical portion of the book to ensure continuity and enhance understanding. Each section includes relevant proofs where appropriate, followed by exercises with useful clues to their solutions. Furthermore, there are brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises are available to instructors in an Answers Manual. This text will appeal to advanced undergraduate and graduate students, as well as researchers and practitioners in engineering, business, social sciences or agriculture. Content, examples, an enhanced number of exercises, and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities Reorganized material in the statistical portion of the book to ensure continuity and enhance understanding A relatively rigorous, yet accessible and always within the prescribed prerequisites, mathematical discussion of probability theory and statistical inference important to students in a broad variety of disciplines Relevant proofs where appropriate in each section, followed by exercises with useful clues to their solutions Brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises available to instructors in an Answers Manual


Author : Lawrence N. Dworsky
Publisher : John Wiley & Sons
Release : 2019-07-29
Page : 352
Category : Mathematics
ISBN 13 : 1119518121
Description :


A revised edition that explores random numbers, probability, and statistical inference at an introductory mathematical level Written in an engaging and entertaining manner, the revised and updated second edition of Probably Not continues to offer an informative guide to probability and prediction. The expanded second edition contains problem and solution sets. In addition, the book’s illustrative examples reveal how we are living in a statistical world, what we can expect, what we really know based upon the information at hand and explains when we only think we know something. The author introduces the principles of probability and explains probability distribution functions. The book covers combined and conditional probabilities and contains a new section on Bayes Theorem and Bayesian Statistics, which features some simple examples including the Presecutor’s Paradox, and Bayesian vs. Frequentist thinking about statistics. New to this edition is a chapter on Benford’s Law that explores measuring the compliance and financial fraud detection using Benford’s Law. This book: Contains relevant mathematics and examples that demonstrate how to use the concepts presented Features a new chapter on Benford’s Law that explains why we find Benford’s law upheld in so many, but not all, natural situations Presents updated Life insurance tables Contains updates on the Gantt Chart example that further develops the discussion of random events Offers a companion site featuring solutions to the problem sets within the book Written for mathematics and statistics students and professionals, the updated edition of Probably Not: Future Prediction Using Probability and Statistical Inference, Second Edition combines the mathematics of probability with real-world examples. LAWRENCE N. DWORSKY, PhD, is a retired Vice President of the Technical Staff and Director of Motorola’s Components Research Laboratory in Schaumburg, Illinois, USA. He is the author of Introduction to Numerical Electrostatics Using MATLAB from Wiley.


Author : Hogg Robert V.
Publisher : Pearson Education India
Release : 2006
Page : 735
Category : Mathematical statistics
ISBN 13 : 9788177585537
Description :



Author : Christopher G. Small
Don L. McLeish
Publisher : John Wiley & Sons
Release : 2011-09-15
Page : 270
Category : Mathematics
ISBN 13 : 1118165535
Description :


Explains how Hilbert space techniques cross the boundaries into the foundations of probability and statistics. Focuses on the theory of martingales stochastic integration, interpolation and density estimation. Includes a copious amount of problems and examples.


Author : Miltiadis C. Mavrakakis
Jeremy Penzer
Publisher : Chapman and Hall/CRC
Release : 2014-12-15
Page : 608
Category : Mathematics
ISBN 13 : 9781584889397
Description :


Modelling, Inference and Data Analysis brings together key topics in mathematical statistics and presents them in a rigorous yet accessible manner. It covers aspects of probability, distribution theory and random processes that are fundamental to a proper understanding of inference. The book also discusses the properties of estimators constructed from a random sample of ends, with sections on methods for estimating parameters in time series models and computationally intensive inferential techniques. The text challenges and excites the more mathematically able students while providing an approachable explanation of advanced statistical concepts for students who struggle with existing texts.


Author : Aris Spanos
Publisher : Cambridge University Press
Release : 2019-08-31
Page : 846
Category : Business & Economics
ISBN 13 : 1107185149
Description :


This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.


Author : J. K. Wani
Publisher : New York : Appleton-Century-Crofts
Release : 1971
Page : 315
Category : Estadística matemática
ISBN 13 :
Description :



Author : James H.C. Creighton
Publisher : Springer Science & Business Media
Release : 2012-12-06
Page : 719
Category : Mathematics
ISBN 13 : 1441985409
Description :


Welcome to new territory: A course in probability models and statistical inference. The concept of probability is not new to you of course. You've encountered it since childhood in games of chance-card games, for example, or games with dice or coins. And you know about the "90% chance of rain" from weather reports. But once you get beyond simple expressions of probability into more subtle analysis, it's new territory. And very foreign territory it is. You must have encountered reports of statistical results in voter sur veys, opinion polls, and other such studies, but how are conclusions from those studies obtained? How can you interview just a few voters the day before an election and still determine fairly closely how HUN DREDS of THOUSANDS of voters will vote? That's statistics. You'll find it very interesting during this first course to see how a properly designed statistical study can achieve so much knowledge from such drastically incomplete information. It really is possible-statistics works! But HOW does it work? By the end of this course you'll have understood that and much more. Welcome to the enchanted forest.


Author : Nitis Mukhopadhyay
Publisher : CRC Press
Release : 2006-02-07
Page : 304
Category : Mathematics
ISBN 13 : 1574446134
Description :


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.


Author : Robert V. Hogg
Elliot A. Tanis
Publisher :
Release : 2013-07-23
Page : 640
Category : Mathematical statistics
ISBN 13 : 9781292024783
Description :


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.


Author : Vijay K. Rohatgi
A.K. Md. Ehsanes Saleh
Publisher : John Wiley & Sons
Release : 2015-08-06
Page : 728
Category : Mathematics
ISBN 13 : 1118799682
Description :


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.