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Books in Statistics and probability

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201-210 of 233 results in All results

Probability - Modular Mathematics Series

  • 1st Edition
  • May 17, 1995
  • John McColl
  • English
  • Paperback
    9 7 8 - 0 - 3 4 0 - 6 1 4 2 6 - 6
Probability is relevant to so many different subject areas that its importance as a mathematical technique cannot be underestimated. This book provides a comprehensive, user-friendly introduction to the subject. The step-by-step approach taken by the author allows students to develop knowledge at their own pace and, by working through the numerous exercises, they are ensured a full understanding of the material before moving on to more advanced sections. Traditional examples of probablistic theory, such as coins and dice, are included but the author has also used many exercises based on real-life problems. The result is an introduction to probability that avoids the overly confusing, theoretical approach often adopted in this area, and provides a simple and concise text that will be invaluable to all studying first and second year courses on the subject.

The Spectral Analysis of Time Series

  • 1st Edition
  • May 8, 1995
  • Lambert H. Koopmans
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 4 1 5 6 - 3
To tailor time series models to a particular physical problem and to follow the working of various techniques for processing and analyzing data, one must understand the basic theory of spectral (frequency domain) analysis of time series. This classic book provides an introduction to the techniques and theories of spectral analysis of time series. In a discursive style, and with minimal dependence on mathematics, the book presents the geometric structure of spectral analysis. This approach makes possible useful, intuitive interpretations of important time series parameters and provides a unified framework for an otherwise scattered collection of seemingly isolated results.The books strength lies in its applicability to the needs of readers from many disciplines with varying backgrounds in mathematics. It provides a solid foundation in spectral analysis for fields that include statistics, signal process engineering, economics, geophysics, physics, and geology. Appendices provide details and proofs for those who are advanced in math. Theories are followed by examples and applications over a wide range of topics such as meteorology, seismology, and telecommunications.Topics covered include Hilbert spaces; univariate models for spectral analysis; multivariate spectral models; sampling, aliasing, and discrete-time models; real-time filtering; digital filters; linear filters; distribution theory; sampling properties ofspectral estimates; and linear prediction.

Statistical Methods in the Atmospheric Sciences

  • 1st Edition
  • Volume 59
  • March 1, 1995
  • Daniel S. Wilks
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 4 1 7 2 - 3
This book introduces and explains the statistical methods used to describe, analyze, test, and forecast atmospheric data. It will be useful to students, scientists, and other professionals who seek to make sense of the scientific literature in meteorology, climatology, or other geophysical disciplines, or to understand and communicate what their atmospheric data sets have to say. The book includes chapters on exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, time(series analysis, and multivariate data analysis. Worked examples, exercises, and illustrations facilitate understanding of the material; an extensive and up-to-date list of references allows the reader to pursue selected topics in greater depth.

Handbook of Econometrics

  • 1st Edition
  • Volume 4
  • December 13, 1994
  • Robert Engle + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 8 8 7 6 6 - 5

Statistical Data Analysis for Ocean and Atmospheric Sciences

  • 1st Edition
  • November 7, 1994
  • H. Jean Thiebaux
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 2 6 2 9 - 2
Studies of local and global phenomena generate descriptions which require statistical analysis. In this text, H. Jean Thiebaux presents a succinct yet comprehensive review of the fundamentals of statistics as they pertain to studies in oceanic and atmospheric sciences. The text includes an accompanying disk with compatible Minitab sample data. Together, this volume and the included data provide insights into the basics of statistical inference, data analysis, and distributional models of variability. Oceanographers, meteorologists, marine biologists, and other environmental scientists will find this book of great value as a statistical tool for their continuing studies.

Estimation Theory in Hydrology and Water Systems

  • 1st Edition
  • Volume 42
  • June 10, 1993
  • K. Nacházel
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 8 7 0 3 3 - 5
Methodological procedures of the theory of estimation of statistical parameters of time series and their application to hydrology and water engineering, particularly the sphere of reservoir-controlled runoffs, are dealt with in this volume. For estimates use is made of random sequences generated for various probability properties. This methodological approach enables examination of the properties of random and systematic errors of the parameters estimated even for the asymmetrical probability distributions, which are frequent in hydrology and water engineering. This book will be of interest to stochastic hydrologists.

Regenerative Stochastic Simulation

  • 1st Edition
  • October 1, 1992
  • Gerald S. Shedler
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 2 5 7 2 - 1
Simulation is a controlled statistical sampling technique that can be used to study complex stochastic systems when analytic and/or numerical techniques do not suffice. The focus of this book is on simulations of discrete-event stochastic systems; namely, simulations in which stochastic state transitions occur only at an increasing sequence of random times. The discussion emphasizes simulations on a finite or countably infinite state space.

Convex Functions, Partial Orderings, and Statistical Applications

  • 1st Edition
  • April 28, 1992
  • Josip E. Peajcariaac + 1 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 2 5 2 2 - 6
This research-level book presents up-to-date information concerning recent developments in convex functions and partial orderings and some applications in mathematics, statistics, and reliability theory. The book will serve researchers in mathematical and statistical theory and theoretical and applied reliabilists.

Probability and Random Processes

  • 1st Edition
  • January 3, 1992
  • Donald Childers + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 1 7 2 6 5 1 - 5
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 7 0 4 2 - 9
Probability and Random Processes provides a clear presentation of foundational concepts with specific applications to signal processing and communications, clearly the two areas of most interest to students and instructors in this course. It includes unique chapters on narrowband random processes and simulation techniques. It also includes applications in digital communications, information theory, coding theory, image processing, speech analysis, synthesis and recognition, and other fields. The appendices provide a refresher in such areas as linear algebra, set theory, random variables, and more. Exceptional exposition and numerous worked out problems make the book extremely readable and accessible. It is meant for practicing engineers as well as graduate students.

Truth, Possibility and Probability

  • 1st Edition
  • Volume 166
  • June 20, 1991
  • R. Chuaqui
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 8 7 2 7 7 - 3
Anyone involved in the philosophy of science is naturally drawn into the study of the foundations of probability. Different interpretations of probability, based on competing philosophical ideas, lead to different statistical techniques, and frequently to mutually contradictory consequences.This unique book presents a new interpretation of probability, rooted in the traditional interpretation that was current in the 17th and 18th centuries. Mathematical models are constructed based on this interpretation, and statistical inference and decision theory are applied, including some examples in artificial intelligence, solving the main foundational problems. Nonstandard analysis is extensively developed for the construction of the models and in some of the proofs. Many nonstandard theorems are proved, some of them new, in particular, a representation theorem that asserts that any stochastic process can be approximated by a process defined over a space with equiprobable outcomes.

Related subjects

Probability theory and stochastic processes

Statistics