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Exercises and solutions in statistical theory / Lawrence L. Kupper, Brian H. Neelon, Sean M. O'Brien.

By: Contributor(s): Material type: TextTextSeries: Chapman & Hall/CRC texts in statistical sciencePublisher: Boca Raton : CRC Press, [2013]Description: 369 pages ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781466572898
Subject(s): LOC classification:
  • QA273.25 .K87 2013
Online resources: Summary: "This book contains exercises and selected detailed solutions covering statistical theory (from basic probability theory through the theory of statistical inference) that is typically taught in courses taken by advanced undergraduate students and graduate students in many quantitative disciplines (e.g., statistics, biostatistics, mathematics, engineering, physics, computer science, psychometrics, epidemiology, etc.). Many exercises in this book deal with real-life scenarios in such important application areas as medicine, epidemiology, clinical trials, actuarial science, social science, psychometrics, parapsychology, engineering, wear testing, lot acceptance sampling, physics, chemistry, biology, environmental health, highway safety research, genetics, gambling, and sports. Several of these exercises illustrate the utility of important statistical areas such as study design strategies, sampling from finite populations, maximum likelihood, asymptotic theory, correlated data analysis, multilevel models, queueing theory, latent class analysis, conditional inference, order statistics, regression analysis, autoregressive models, survival analysis, generalized linear models, Bayesian analysis, measurement and misclassification error, group testing, and interrater agreement methods. Numerous exercises contain references to published books and articles that both students and instructors can use to obtain more information about the particular statistical topics being considered"-- Provided by publisher.
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"This book contains exercises and selected detailed solutions covering statistical theory (from basic probability theory through the theory of statistical inference) that is typically taught in courses taken by advanced undergraduate students and graduate students in many quantitative disciplines (e.g., statistics, biostatistics, mathematics, engineering, physics, computer science, psychometrics, epidemiology, etc.). Many exercises in this book deal with real-life scenarios in such important application areas as medicine, epidemiology, clinical trials, actuarial science, social science, psychometrics, parapsychology, engineering, wear testing, lot acceptance sampling, physics, chemistry, biology, environmental health, highway safety research, genetics, gambling, and sports. Several of these exercises illustrate the utility of important statistical areas such as study design strategies, sampling from finite populations, maximum likelihood, asymptotic theory, correlated data analysis, multilevel models, queueing theory, latent class analysis, conditional inference, order statistics, regression analysis, autoregressive models, survival analysis, generalized linear models, Bayesian analysis, measurement and misclassification error, group testing, and interrater agreement methods. Numerous exercises contain references to published books and articles that both students and instructors can use to obtain more information about the particular statistical topics being considered"-- Provided by publisher.

Includes bibliographical references and index.

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