Exercises And Solutions In Biostatistical Theory PDF Download
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| Author | : Lawrence Kupper |
| Publisher | : CRC Press |
| Total Pages | : 422 |
| Release | : 2010-11-09 |
| Genre | : Mathematics |
| ISBN | : 1584887222 |
Download Exercises and Solutions in Biostatistical Theory Book in PDF, ePub and Kindle
Drawn from nearly four decades of Lawrence L. Kupper’s teaching experiences as a distinguished professor in the Department of Biostatistics at the University of North Carolina, Exercises and Solutions in Biostatistical Theory presents theoretical statistical concepts, numerous exercises, and detailed solutions that span topics from basic probability to statistical inference. The text links theoretical biostatistical principles to real-world situations, including some of the authors’ own biostatistical work that has addressed complicated design and analysis issues in the health sciences. This classroom-tested material is arranged sequentially starting with a chapter on basic probability theory, followed by chapters on univariate distribution theory and multivariate distribution theory. The last two chapters on statistical inference cover estimation theory and hypothesis testing theory. Each chapter begins with an in-depth introduction that summarizes the biostatistical principles needed to help solve the exercises. Exercises range in level of difficulty from fairly basic to more challenging (identified with asterisks). By working through the exercises and detailed solutions in this book, students will develop a deep understanding of the principles of biostatistical theory. The text shows how the biostatistical theory is effectively used to address important biostatistical issues in a variety of real-world settings. Mastering the theoretical biostatistical principles described in the book will prepare students for successful study of higher-level statistical theory and will help them become better biostatisticians.
| Author | : Lawrence L. Kupper |
| Publisher | : CRC Press |
| Total Pages | : 384 |
| Release | : 2013-06-24 |
| Genre | : Mathematics |
| ISBN | : 1466572906 |
Download Exercises and Solutions in Statistical Theory Book in PDF, ePub and Kindle
Exercises and Solutions in Statistical Theory helps students and scientists obtain an in-depth understanding of statistical theory by working on and reviewing solutions to interesting and challenging exercises of practical importance. Unlike similar books, this text incorporates many exercises that apply to real-world settings and provides much mor
| Author | : Felix Abramovich |
| Publisher | : CRC Press |
| Total Pages | : 240 |
| Release | : 2013-04-25 |
| Genre | : Mathematics |
| ISBN | : 148221184X |
Download Statistical Theory Book in PDF, ePub and Kindle
Designed for a one-semester advanced undergraduate or graduate course, Statistical Theory: A Concise Introduction clearly explains the underlying ideas and principles of major statistical concepts, including parameter estimation, confidence intervals, hypothesis testing, asymptotic analysis, Bayesian inference, and elements of decision theory. It i
| Author | : Peihua Qiu |
| Publisher | : CRC Press |
| Total Pages | : 523 |
| Release | : 2013-10-14 |
| Genre | : Business & Economics |
| ISBN | : 1439847991 |
Download Introduction to Statistical Process Control Book in PDF, ePub and Kindle
A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon the more established techniques. The author—a leading researcher on SPC—shows how these methods can handle new applications. After exploring the role of SPC and other statistical methods in quality control and management, the book covers basic statistical concepts and methods useful in SPC. It then systematically describes traditional SPC charts, including the Shewhart, CUSUM, and EWMA charts, as well as recent control charts based on change-point detection and fundamental multivariate SPC charts under the normality assumption. The text also introduces novel univariate and multivariate control charts for cases when the normality assumption is invalid and discusses control charts for profile monitoring. All computations in the examples are solved using R, with R functions and datasets available for download on the author’s website. Offering a systematic description of both traditional and newer SPC methods, this book is ideal as a primary textbook for a one-semester course in disciplines concerned with process quality control, such as statistics, industrial and systems engineering, and management sciences. It can also be used as a supplemental textbook for courses on quality improvement and system management. In addition, the book provides researchers with many useful, recent research results on SPC and gives quality control practitioners helpful guidelines on implementing up-to-date SPC techniques.
| Author | : Athanasios Christou Micheas |
| Publisher | : CRC Press |
| Total Pages | : 409 |
| Release | : 2018-01-19 |
| Genre | : Mathematics |
| ISBN | : 146651521X |
Download Theory of Stochastic Objects Book in PDF, ePub and Kindle
This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks; one would need material on real analysis, measure and probability theory, as well as stochastic processes - in addition to at least one text on statistics- to capture the detail and depth of material that has gone into this volume. Presents and illustrates ‘random objects’ in different contexts, under a unified framework, starting with rudimentary results on random variables and random sequences, all the way up to stochastic partial differential equations. Reviews rudimentary probability and introduces statistical inference, from basic to advanced, thus making the transition from basic statistical modeling and estimation to advanced topics more natural and concrete. Compact and comprehensive presentation of the material that will be useful to a reader from the mathematics and statistical sciences, at any stage of their career, either as a graduate student, an instructor, or an academician conducting research and requiring quick references and examples to classic topics. Includes 378 exercises, with the solutions manual available on the book's website. 121 illustrative examples of the concepts presented in the text (many including multiple items in a single example). The book is targeted towards students at the master’s and Ph.D. levels, as well as, academicians in the mathematics, statistics and related disciplines. Basic knowledge of calculus and matrix algebra is required. Prior knowledge of probability or measure theory is welcomed but not necessary.
| Author | : Michael A. Proschan |
| Publisher | : CRC Press |
| Total Pages | : 328 |
| Release | : 2018-09-03 |
| Genre | : Mathematics |
| ISBN | : 131536235X |
Download Essentials of Probability Theory for Statisticians Book in PDF, ePub and Kindle
Essentials of Probability Theory for Statisticians provides graduate students with a rigorous treatment of probability theory, with an emphasis on results central to theoretical statistics. It presents classical probability theory motivated with illustrative examples in biostatistics, such as outlier tests, monitoring clinical trials, and using adaptive methods to make design changes based on accumulating data. The authors explain different methods of proofs and show how they are useful for establishing classic probability results. After building a foundation in probability, the text intersperses examples that make seemingly esoteric mathematical constructs more intuitive. These examples elucidate essential elements in definitions and conditions in theorems. In addition, counterexamples further clarify nuances in meaning and expose common fallacies in logic. This text encourages students in statistics and biostatistics to think carefully about probability. It gives them the rigorous foundation necessary to provide valid proofs and avoid paradoxes and nonsensical conclusions.
| Author | : Wayne W. Daniel |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2006-05 |
| Genre | : |
| ISBN | : 9780471746522 |
Download Biostatistics, Textbook and Student Solutions Manual Book in PDF, ePub and Kindle
Using an applied and computer oriented approach, this book presents examples and exercises that make use of real data from actual research projects and reports from health sciences literature. It also includes where appropriate, Minitab, SPSS and SAS commands and printouts as part of the examples and solutions to exercises.
| Author | : Randal Douc |
| Publisher | : CRC Press |
| Total Pages | : 548 |
| Release | : 2014-01-06 |
| Genre | : Mathematics |
| ISBN | : 1466502347 |
Download Nonlinear Time Series Book in PDF, ePub and Kindle
This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference.
| Author | : Piotr Kokoszka |
| Publisher | : CRC Press |
| Total Pages | : 307 |
| Release | : 2017-09-27 |
| Genre | : Mathematics |
| ISBN | : 1498746624 |
Download Introduction to Functional Data Analysis Book in PDF, ePub and Kindle
Introduction to Functional Data Analysis provides a concise textbook introduction to the field. It explains how to analyze functional data, both at exploratory and inferential levels. It also provides a systematic and accessible exposition of the methodology and the required mathematical framework. The book can be used as textbook for a semester-long course on FDA for advanced undergraduate or MS statistics majors, as well as for MS and PhD students in other disciplines, including applied mathematics, environmental science, public health, medical research, geophysical sciences and economics. It can also be used for self-study and as a reference for researchers in those fields who wish to acquire solid understanding of FDA methodology and practical guidance for its implementation. Each chapter contains plentiful examples of relevant R code and theoretical and data analytic problems. The material of the book can be roughly divided into four parts of approximately equal length: 1) basic concepts and techniques of FDA, 2) functional regression models, 3) sparse and dependent functional data, and 4) introduction to the Hilbert space framework of FDA. The book assumes advanced undergraduate background in calculus, linear algebra, distributional probability theory, foundations of statistical inference, and some familiarity with R programming. Other required statistics background is provided in scalar settings before the related functional concepts are developed. Most chapters end with references to more advanced research for those who wish to gain a more in-depth understanding of a specific topic.
| Author | : Vidyadhar G. Kulkarni |
| Publisher | : CRC Press |
| Total Pages | : 606 |
| Release | : 2016-11-18 |
| Genre | : Business & Economics |
| ISBN | : 149875662X |
Download Modeling and Analysis of Stochastic Systems Book in PDF, ePub and Kindle
Building on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.
