Updated in a new 12th edition, Human Communication: The Basic Course surveys the broad field of human communication, giving attention to theory, research, and skill development. This book provides an in-depth look at the concepts, principles, and skills of human communication, emphasizing public speaking, interpersonal communication, and small group communication.

Human Communication: The Basic Course: International Edition

Billingsley, Patrick

Huntsberger, David V.

Allyn& B

Brief Business Statistics

Watson, Collin

Croft, D. James

Huntsberger, David

Business & Money

Pearson Higher Education

PROBABILITY AND MEASURE Third Edition Now in its new third edition, Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Retaining the unique approach of the previous editions, this text interweaves material on probability and measure, so that probability problems generate an interest in measure theory and measure theory is then developed and applied to probability. Probability and Measure provides thorough coverage of probability, measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability, and stochastic processes. The Third Edition features an improved treatment of Brownian motion and the replacement of queuing theory with ergodic theory. Like the previous editions, this new edition will be well received by students of mathematics, statistics, economics, and a wide variety of disciplines that require a solid understanding of probability theory.

Probability and Measure

Science & Math

Mathematics

Wiley-Interscience

Convergence of Probability Measures (Wiley Series in Probability and Mathematical Statistics)

wiley

1965: by Patrick Bilingsley - 193 pages - Published by John Wiley & Sons.

Ergodic Theory and Information ( Wiley Series in Probability and Mathematical Statistics)

John Wiley&Sons

A new look at weak-convergence methods in metric spaces-from a master of probability theory In this new edition, Patrick Billingsley updates his classic work Convergence of Probability Measures to reflect developments of the past thirty years. Widely known for his straightforward approach and reader-friendly style, Dr. Billingsley presents a clear, precise, up-to-date account of probability limit theory in metric spaces. He incorporates many examples and applications that illustrate the power and utility of this theory in a range of disciplines-from analysis and number theory to statistics, engineering, economics, and population biology. With an emphasis on the simplicity of the mathematics and smooth transitions between topics, the Second Edition boasts major revisions of the sections on dependent random variables as well as new sections on relative measure, on lacunary trigonometric series, and on the Poisson-Dirichlet distribution as a description of the long cycles in permutations and the large divisors of integers. Assuming only standard measure-theoretic probability and metric-space topology, Convergence of Probability Measures provides statisticians and mathematicians with basic tools of probability theory as well as a springboard to the "industrial-strength" literature available today.

Convergence of Probability Measures

A senior-graduate level text and reference that links the disciplines of probability and measure theory. Including many practical problems and examples, it begins with an introduction to Borel's normal number theorem, proved by calculus alone, followed by short sections that establish the existence and fundamental properties of probability measures, including Lebesque measure on the unit interval. Coverage includes topics in measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability, and stochastic processes.

Probability and Measure (Wiley Series in Probability and Statistics)

Elements of Statistical Inference

William C Brown Pub

Ergodic theory and information

Robert E. Krieger

A treatment of the convergence of probability measures from the foundations to applications in limit theory for dependent random variables. Mapping theorems are proved via Skorokhod's representation theorem; Prokhorov's theorem is proved by construction of a content. The limit theorems at the conclusion are proved under a new set of conditions that apply fairly broadly, but at the same time make possible relatively simple proofs.

Weak Convergence of Measures: Applications in Probability (CBMS-NSF Regional Conference Series in Applied Mathematics, Series Number 5)

Society for Industrial and Applied Mathematics

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Books by Billingsley, Patrick