# Search Results for "intro-to-probability-vol-2-2e-v-2-wiley-series-in-probability-and-statistics"

## Causal Inference in Statistics, Social, and Biomedical Sciences

**Author**: Guido W. Imbens,Donald B. Rubin**Publisher:**Cambridge University Press**ISBN:**0521885884**Category:**Business & Economics**Page:**625**View:**5356

This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

## An Introduction to Probability and Statistics

**Author**: Vijay K. Rohatgi,A.K. Md. Ehsanes Saleh**Publisher:**John Wiley & Sons**ISBN:**1118799658**Category:**Mathematics**Page:**728**View:**2365

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.

## Philosophical Lectures on Probability

*collected, edited, and annotated by Alberto Mura*

**Author**: Bruno de Finetti**Publisher:**Springer Science & Business Media**ISBN:**1402082029**Category:**Science**Page:**216**View:**9206

Bruno de Finetti (1906–1985) is the founder of the subjective interpretation of probability, together with the British philosopher Frank Plumpton Ramsey. His related notion of “exchangeability” revolutionized the statistical methodology. This book (based on a course held in 1979) explains in a language accessible also to non-mathematicians the fundamental tenets and implications of subjectivism, according to which the probability of any well specified fact F refers to the degree of belief actually held by someone, on the ground of her whole knowledge, on the truth of the assertion that F obtains.

## Lectures in Mathematical Statistics

*Parts 1 and 2*

**Author**: I͡U. N. Linʹkov**Publisher:**American Mathematical Soc.**ISBN:**9780821889688**Category:**Mathematics**Page:**321**View:**8763

This volume is intended for the advanced study of several topics in mathematical statistics. The first part of the book is devoted to sampling theory (from one-dimensional and multidimensional distributions), asymptotic properties of sampling, parameter estimation, sufficient statistics, and statistical estimates. The second part is devoted to hypothesis testing and includes the discussion of families of statistical hypotheses that can be asymptotically distinguished. In particular,the author describes goodness-of-fit and sequential statistical criteria (Kolmogorov, Pearson, Smirnov, and Wald) and studies their main properties. The book is suitable for graduate students and researchers interested in mathematical statistics. It is useful for independent study or supplementaryreading.

## Probability Theory

**Author**: Alexandr A. Borovkov**Publisher:**Springer Science & Business Media**ISBN:**1447152018**Category:**Mathematics**Page:**733**View:**4172

This self-contained, comprehensive book tackles the principal problems and advanced questions of probability theory and random processes in 22 chapters, presented in a logical order but also suitable for dipping into. They include both classical and more recent results, such as large deviations theory, factorization identities, information theory, stochastic recursive sequences. The book is further distinguished by the inclusion of clear and illustrative proofs of the fundamental results that comprise many methodological improvements aimed at simplifying the arguments and making them more transparent. The importance of the Russian school in the development of probability theory has long been recognized. This book is the translation of the fifth edition of the highly successful Russian textbook. This edition includes a number of new sections, such as a new chapter on large deviation theory for random walks, which are of both theoretical and applied interest. The frequent references to Russian literature throughout this work lend a fresh dimension and make it an invaluable source of reference for Western researchers and advanced students in probability related subjects. Probability Theory will be of interest to both advanced undergraduate and graduate students studying probability theory and its applications. It can serve as a basis for several one-semester courses on probability theory and random processes as well as self-study.

## Books in Series

**Author**: N.A**Publisher:**N.A**ISBN:**9780835221092**Category:**Monographic series**Page:**1756**View:**9361

## Books in Series in the United States

**Author**: N.A**Publisher:**N.A**ISBN:**N.A**Category:**Children's literature in series**Page:**N.A**View:**1650

## BPR

**Author**: N.A**Publisher:**N.A**ISBN:**N.A**Category:**American literature**Page:**N.A**View:**8596

## Rough Set Theory and Granular Computing

**Author**: Masahiro Inuiguchi,Shoji Hirano**Publisher:**Springer Science & Business Media**ISBN:**9783540005742**Category:**Computers**Page:**300**View:**9180

This monograph presents novel approaches and new results in fundamentals and applications related to rough sets and granular computing. It includes the application of rough sets to real world problems, such as data mining, decision support and sensor fusion. The relationship of rough sets to other important methods of data analysis – Bayes theorem, neurocomputing and pattern recognition is thoroughly examined. Another issue is the rough set based data analysis, including the study of decision making in conflict situations. Recent engineering applications of rough set theory are given, including a processor architecture organization for fast implementation of basic rough set operations and results concerning advanced image processing for unmanned aerial vehicles. New emerging areas of study and applications are presented as well as a wide spectrum of on-going research, which makes the book valuable to all interested in the field of rough set theory and granular computing.