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51-60 of 145 results in All results

Mathematical Statistics with Applications in R

  • 2nd Edition
  • August 18, 2014
  • Kandethody M. Ramachandran + 1 more
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 4 1 7 1 3 2 - 9
Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner.This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students.Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies.

Introduction to Probability and Statistics for Engineers and Scientists

  • 5th Edition
  • August 14, 2014
  • Sheldon M. Ross
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 3 9 4 8 4 2 - 7
Introduction to Probability and Statistics for Engineers and Scientists, Fifth Edition is a proven text reference that provides a superior introduction to applied probability and statistics for engineering or science majors. The book lays emphasis in the manner in which probability yields insight into statistical problems, ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data from actual studies across life science, engineering, computing and business are incorporated in a wide variety of exercises and examples throughout the text. These examples and exercises are combined with updated problem sets and applications to connect probability theory to everyday statistical problems and situations. The book also contains end of chapter review material that highlights key ideas as well as the risks associated with practical application of the material. Furthermore, there are new additions to proofs in the estimation section as well as new coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions. This text is intended for upper level undergraduate and graduate students taking a course in probability and statistics for science or engineering, and for scientists, engineers, and other professionals seeking a reference of foundational content and application to these fields.

Systematic Glossary of the Terminology of Statistical Methods

  • 1st Edition
  • June 28, 2014
  • I. Paenson
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 6 2 1 - 0
Systematic Glossary of the Terminology of Statistical Methods focuses on the elaboration of terms used in statistical methods. The publication first elaborates on the subject and basic methods of statistics, collection of statistical data, and classification and tabulation of statistical data. Discussions focus on the basic methods of statistics, units used in statistics, statistical inquiry, and the subject of statistics. The text then ponders on graphic presentation, averages, and measurements of variation. The manuscript examines essential theoretical distributions, moments of a frequency distribution, and statistical inference. Topics include point and interval estimations, binomial and normal distributions, nature of theoretical distributions, and elements of the theory of probability. The text also evaluates the theory of attributes, correlation, analysis of variance, and time series, including decomposition of time series, multiple correlation, and variance analysis with two or more principles of classification. The publication is a valuable reference for readers interested in the terms used in statistical methods.

Order Statistics & Inference

  • 1st Edition
  • June 28, 2014
  • Narayanaswamy Balakrishnan + 1 more
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 7 4 9 - 1
The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology,a nd electrical and chemical engineering. A complete, comprehensive bibliography is included so the book can be used both aas a text and reference.

Statistical Inferences for Stochasic Processes

  • 1st Edition
  • June 28, 2014
  • Ishwar V. Basawa
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 6 1 4 - 2
Statistical Inference Stochastic Processes provides information pertinent to the theory of stochastic processes. This book discusses stochastic models that are increasingly used in scientific research and describes some of their applications. Organized into three parts encompassing 12 chapters, this book begins with an overview of the basic concepts and procedures of statistical inference. This text then explains the inference problems for Galton–Watson process for discrete time and Markov-branching processes for continuous time. Other chapters consider problems of prediction, filtering, and parameter estimation for some simple discrete-time linear stochastic processes. This book discusses as well the ergodic type chains with finite and countable state-spaces and describes some results on birth and death processes that are of a non-ergodic type. The final chapter deals with inference procedures for stochastic processes through sequential procedures. This book is a valuable resource for graduate students.

Introduction to Structural Equation Models

  • 1st Edition
  • June 28, 2014
  • Otis Dudley Duncan
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 5 3 2 - 9
Introduction to Structural Equation Models prepares the reader to understand the recent sociological literature on the use of structural equation models in research, and discusses methodological questions pertaining to such models. The material in first seven chapters is almost entirely standard, with the remaining four introducing progressively more open-ended issues, seducing the reader into beginning to think for himself about the properties of models or even to suggest problems that may intrigue the advanced student.

Statistical Methods in Longitudinal Research

  • 1st Edition
  • Volume 1
  • June 28, 2014
  • Alexander von Eye
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 7 9 5 - 8
These edited volumes present new statistical methods in a way that bridges the gap between theoretical and applied statistics. The volumes cover general problems and issues and more specific topics concerning the structuring of change, the analysis of time series, and the analysis of categorical longitudinal data. The book targets students of development and change in a variety of fields - psychology, sociology, anthropology, education, medicine, psychiatry, economics, behavioural sciences, developmental psychology, ecology, plant physiology, and biometry - with basic training in statistics and computing.

Fundamentals of Applied Probability and Random Processes

  • 2nd Edition
  • June 13, 2014
  • Oliver Ibe
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 0 0 8 5 2 - 2
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 1 0 3 5 - 8
The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study.

Statistical Data Analysis and Inference

  • 1st Edition
  • May 23, 2014
  • Y. Dodge
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 6 1 1 - 1
A wide range of topics and perspectives in the field of statistics are brought together in this volume. The contributions originate from invited papers presented at an international conference which was held in honour of C. Radhakrishna Rao, one of the most eminent statisticians of our time and a distinguished scientist.

Multivariate Analysis: Future Directions 2

  • 1st Edition
  • Volume 5
  • May 21, 2014
  • C.M. Cuadras + 1 more
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 7 5 6 - 9
The contributions in this volume, made by distinguished statisticians in several frontier areas of research in multivariate analysis, cover a broad field and indicate future directions of research. The topics covered include discriminant analysis, multidimensional scaling, categorical data analysis, correspondence analysis and biplots, association analysis, latent variable models, bootstrap distributions, differential geometry applications and others. Most of the papers propose generalizations or new applications of multivariate analysis.This volume will be of great interest to statisticians, probabilists, data analysts and scientists working in the disciplines such as biology, biometry, ecology, medicine, econometry, psychometry and marketing. It will be a valuable guide to professors, researchers and graduate students seeking new and promising lines of statistical research.