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101-110 of 145 results in All results

Handbook of Latent Variable and Related Models

  • 1st Edition
  • Volume 1
  • February 8, 2007
  • Sik-Yum Lee
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 7 1 2 6 - 6
This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.

Biostatistics

  • 2nd Edition
  • December 14, 2006
  • Ronald N. Forthofer + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 3 6 9 4 9 2 - 8
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 6 7 7 2 - 6
Biostatistics, Second Edition, is a user-friendly guide on biostatistics, which focuses on the proper use and interpretation of statistical methods. This textbook does not require extensive background in mathematics, making it user-friendly for all students in the public health sciences field. Instead of highlighting derivations of formulas, the authors provide rationales for the formulas, allowing students to grasp a better understanding of the link between biology and statistics. The material on life tables and survival analysis allows students to better understand the recent literature in the health field, particularly in the study of chronic disease treatment. This updated edition contains over 40% new material with modern real-life examples, exercises, and references, including new chapters on Logistic Regression, Analysis of Survey Data, and Study Designs. The book is recommended for students in the health sciences, public health professionals, and practitioners.

Psychometrics

  • 1st Edition
  • Volume 26
  • November 8, 2006
  • C.R. Rao + 1 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 6 6 7 0 - 5
The area of Psychometrics, a field encompassing the statistical methods used in Psychological and educational testing, has become a very important and active area of research, evident from the large body of literature that has been developed in the form of books, volumes and research papers.Mainstream statisticians also have found profound interest in the field because of its unique nature.This book presents a state of the art exposition of theoretical, methodological and applied issues in Psychometrics. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with recent challenging psychometric problems.Key Features/- Emphasis on the most recent developments in the field- Plenty of real, often complicated, data examples to demonstrate the applications of the statistical techniques- Information on available software

Information-Theoretic Methods for Estimating of Complicated Probability Distributions

  • 1st Edition
  • Volume 207
  • August 15, 2006
  • Zhi Zong
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 6 3 8 5 - 8
Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions.Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neural networks and quality control. Simple distribution forms such as Gaussian, exponential or Weibull distributions are often employed to represent the distributions of the random variables under consideration, as we are taught in universities. In engineering, physical and social science applications, however, the distributions of many random variables or random vectors are so complicated that they do not fit the simple distribution forms at al.Exact estimation of the probability distribution of a random variable is very important. Take stock market prediction for example. Gaussian distribution is often used to model the fluctuations of stock prices. If such fluctuations are not normally distributed, and we use the normal distribution to represent them, how could we expect our prediction of stock market is correct? Another case well exemplifying the necessity of exact estimation of probability distributions is reliability engineering. Failure of exact estimation of the probability distributions under consideration may lead to disastrous designs.There have been constant efforts to find appropriate methods to determine complicated distributions based on random samples, but this topic has never been systematically discussed in detail in a book or monograph. The present book is intended to fill the gap and documents the latest research in this subject.Determining a complicated distribution is not simply a multiple of the workload we use to determine a simple distribution, but it turns out to be a much harder task. Two important mathematical tools, function approximation and information theory, that are beyond traditional mathematical statistics, are often used. Several methods constructed based on the two mathematical tools for distribution estimation are detailed in this book. These methods have been applied by the author for several years to many cases. They are superior in the following senses:(1) No prior information of the distribution form to be determined is necessary. It can be determined automatically from the sample;(2) The sample size may be large or small;(3) They are particularly suitable for computers. It is the rapid development of computing technology that makes it possible for fast estimation of complicated distributions. The methods provided herein well demonstrate the significant cross influences between information theory and statistics, and showcase the fallacies of traditional statistics that, however, can be overcome by information theory.Key Features:- Density functions automatically determined from samples- Free of assuming density forms- Computation-effective methods suitable for PC

Simulation

  • 4th Edition
  • August 1, 2006
  • Sheldon M. Ross
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 1 7 2 2 - 3
Ross's Simulation, Fourth Edition introduces aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes. This text explains how a computer can be used to generate random numbers, and how to use these random numbers to generate the behavior of a stochastic model over time. It presents the statistics needed to analyze simulated data as well as that needed for validating the simulation model.

Regression Analysis

  • 2nd Edition
  • March 27, 2006
  • Rudolf J. Freund + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 0 8 8 5 9 7 - 8
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 2 2 9 7 - 5
Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design.

Bayesian Thinking, Modeling and Computation

  • 1st Edition
  • Volume 25
  • November 29, 2005
  • Dipak K. Dey + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 5 1 5 3 9 - 1
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 6 1 1 7 - 5
This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians.

Advanced Statistics from an Elementary Point of View

  • 1st Edition
  • October 14, 2005
  • Michael J Panik
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 0 8 8 4 9 4 - 0
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 7 0 3 0 - 3
Advanced Statistics from an Elementary Point of View is a highly readable text that communicates the content of a course in mathematical statistics without imposing too much rigor. It clearly emphasizes the connection between statistics and probability, and helps students concentrate on statistical strategies without being overwhelmed by calculations. The book provides comprehensive coverage of descriptive statistics; detailed treatment of univariate and bivariate probability distributions; and thorough coverage of probability theory with numerous event classifications. This book is designed for statistics majors who are already familiar with introductory calculus and statistics, and can be used in either a one- or two-semester course. It can also serve as a statistics tutorial or review for working professionals. Students who use this book will be well on their way to thinking like a statistician in terms of problem solving and decision-making. Graduates who pursue careers in statistics will continue to find this book useful, due to numerous statistical test procedures (both parametric and non-parametric) and detailed examples.

Student Solutions Manual for Introductory Statistics

  • 2nd Edition
  • October 11, 2005
  • Sheldon M. Ross
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 0 8 8 5 5 1 - 0
This handy supplement shows students how to come to the answers shown in the back of the text. It includes solutions to all of the odd numbered exercises. The text itself:In this second edition, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, examples and applications from diverse areas, and most importantly, an explanation of intuition and ideas behind the statistical methods. To quote from the preface, "it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data." Consistent with his other excellent books in Probability and Stochastic Modeling, Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples.

Statistics in Medicine

  • 2nd Edition
  • August 4, 2005
  • Robert H. Riffenburgh
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 4 1 7 4 - 7
Medicine deals with treatments that work often but not always, so treatment success must be based on probability. Statistical methods lift medical research from the anecdotal to measured levels of probability. This book presents the common statistical methods used in 90% of medical research, along with the underlying basics, in two parts: a textbook section for use by students in health care training programs, e.g., medical schools or residency training, and a reference section for use by practicing clinicians in reading medical literature and performing their own research. The book does not require a significant level of mathematical knowledge and couches the methods in multiple examples drawn from clinical medicine, giving it applicable context.