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Books in Statistics and probability

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Essential Bayesian Models

  • 1st Edition
  • November 17, 2010
  • C.R. Rao + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 5 3 7 3 2 - 4
This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric Bayesian methods for modeling, and how to use modern computational methods to summarize inferences using simulation. The book covers a wide range of topics including objective and subjective Bayesian inferences, with a variety of applications in modeling categorical, survival, spatial, spatiotemporal, Epidemiological, small area and micro array data.

Doing Bayesian Data Analysis

  • 1st Edition
  • October 27, 2010
  • John Kruschke
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 3 8 1 4 8 6 - 9
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and ‘rusty’ calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a large variety of students and their own research needs.The textbook bridges the students from their undergraduate training into modern Bayesian methods.

Statistical Methods

  • 3rd Edition
  • July 6, 2010
  • Donna L. Mohr
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 6 1 0 3 - 3
Statistical Methods, Third Edition, provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach that emphasizes concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies, numerous examples, and data exercises organized by level of difficulty. Students are required to be familiar with algebra. This updated edition includes new exercises applying different techniques and methods; new examples and datasets using current real-world data; new text organization to create a more natural connection between regression and the Analysis of the Variance; new material on generalized linear models; new expansion of nonparametric techniques; new student research projects; and new case studies for gathering, summarizing, and analyzing data.

Introductory Statistics

  • 3rd Edition
  • January 19, 2010
  • Sheldon M. Ross
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 2 2 1 0 - 2
Introductory Statistics, Third Edition, presents statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also to understand why these procedures should be used. This book offers a unique historical perspective, profiling prominent statisticians and historical events in order to motivate learning. To help guide students towards independent learning, exercises and examples using real issues and real data (e.g., stock price models, health issues, gender issues, sports, scientific fraud) are provided. The chapters end with detailed reviews of important concepts and formulas, key terms, and definitions that are useful study tools. Data sets from text and exercise material are available for download in the text website. This text is designed for introductory non-calculus based statistics courses that are offered by mathematics and/or statistics departments to undergraduate students taking a semester course in basic Statistics or a year course in Probability and Statistics.

Sample Surveys: Inference and Analysis

  • 1st Edition
  • Volume 29B
  • September 2, 2009
  • Danny Pfeffermann + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 5 3 4 3 8 - 5
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 6 3 5 4 - 9
Handbook of Statistics_29B contains the most comprehensive account of sample surveys theory and practice to date. It is a second volume on sample surveys, with the goal of updating and extending the sampling volume published as volume 6 of the Handbook of Statistics in 1988. The present handbook is divided into two volumes (29A and 29B), with a total of 41 chapters, covering current developments in almost every aspect of sample surveys, with references to important contributions and available software. It can serve as a self contained guide to researchers and practitioners, with appropriate balance between theory and real life applications. Each of the two volumes is divided into three parts, with each part preceded by an introduction, summarizing the main developments in the areas covered in that part. Volume 1 deals with methods of sample selection and data processing, with the later including editing and imputation, handling of outliers and measurement errors, and methods of disclosure control. The volume contains also a large variety of applications in specialized areas such as household and business surveys, marketing research, opinion polls and censuses. Volume 2 is concerned with inference, distinguishing between design-based and model-based methods and focusing on specific problems such as small area estimation, analysis of longitudinal data, categorical data analysis and inference on distribution functions. The volume contains also chapters dealing with case-control studies, asymptotic properties of estimators and decision theoretic aspects.

Sample Surveys: Design, Methods and Applications

  • 1st Edition
  • Volume 29A
  • August 31, 2009
  • Danny Pfeffermann + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 5 3 1 2 4 - 7
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 3 2 2 1 - 7
This new handbook contains the most comprehensive account of sample surveys theory and practice to date. It is a second volume on sample surveys, with the goal of updating and extending the sampling volume published as volume 6 of the Handbook of Statistics in 1988. The present handbook is divided into two volumes (29A and 29B), with a total of 41 chapters, covering current developments in almost every aspect of sample surveys, with references to important contributions and available software. It can serve as a self contained guide to researchers and practitioners, with appropriate balance between theory and real life applications. Each of the two volumes is divided into three parts, with each part preceded by an introduction, summarizing the main developments in the areas covered in that part. Volume 29A deals with methods of sample selection and data processing, with the later including editing and imputation, handling of outliers and measurement errors, and methods of disclosure control. The volume contains also a large variety of applications in specialized areas such as household and business surveys, marketing research, opinion polls and censuses. Volume 29B is concerned with inference, distinguishing between design-based and model-based methods and focusing on specific problems such as small area estimation, analysis of longitudinal data, categorical data analysis and inference on distribution functions. The volume contains also chapters dealing with case-control studies, asymptotic properties of estimators and decision theoretic aspects.

Handbook of Statistical Analysis and Data Mining Applications

  • 1st Edition
  • May 14, 2009
  • Robert Nisbet + 2 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 1 2 0 3 - 5
The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions.

Markov Processes for Stochastic Modeling

  • 1st Edition
  • September 2, 2008
  • Oliver Ibe
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 9 2 2 4 5 - 4
Markov processes are used to model systems with limited memory. They are used in many areas including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. This book, which is written for upper level undergraduate and graduate students, and researchers, presents a unified presentation of Markov processes. In addition to traditional topics such as Markovian queueing system, the book discusses such topics as continuous-time random walk,correlated random walk, Brownian motion, diffusion processes, hidden Markov models, Markov random fields, Markov point processes and Markov chain Monte Carlo. Continuous-time random walk is currently used in econophysics to model the financial market, which has traditionally been modelled as a Brownian motion. Correlated random walk is popularly used in ecological studies to model animal and insect movement. Hidden Markov models are used in speech analysis and DNA sequence analysis while Markov random fields and Markov point processes are used in image analysis. Thus, the book is designed to have a very broad appeal.

Epidemiology and Medical Statistics

  • 1st Edition
  • Volume 27
  • November 6, 2007
  • C.R. Rao + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 5 2 8 0 1 - 8
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 5 4 2 1 - 1
This volume, representing a compilation of authoritative reviews on a multitude of uses of statistics in epidemiology and medical statistics written by internationally renowned experts, is addressed to statisticians working in biomedical and epidemiological fields who use statistical and quantitative methods in their work. While the use of statistics in these fields has a long and rich history, explosive growth of science in general and clinical and epidemiological sciences in particular have gone through a see of change, spawning the development of new methods and innovative adaptations of standard methods. Since the literature is highly scattered, the Editors have undertaken this humble exercise to document a representative collection of topics of broad interest to diverse users. The volume spans a cross section of standard topics oriented toward users in the current evolving field, as well as special topics in much need which have more recent origins. This volume was prepared especially keeping the applied statisticians in mind, emphasizing applications-oriented methods and techniques, including references to appropriate software when relevant.

Related subjects

Probability theory and stochastic processes

Statistics