Modern Statistics for the Life Sciences

Modern Statistics for the Life Sciences

Author: Alan Grafen

Publisher: Oxford University Press

Published: 2002-03-21

Total Pages: 368

ISBN-13: 0199252319

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Model formulae represent a powerful methodology for describing, discussing, understanding, and performing that large part of statistical tests known as linear statistics. The book aims to put this methodology firmly within the grasp of undergraduates.


The Practice of Statistics in the Life Sciences

The Practice of Statistics in the Life Sciences

Author: Brigitte Baldi

Publisher: Macmillan Higher Education

Published: 2013-12-15

Total Pages: 756

ISBN-13: 1464133212

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This remarkably engaging textbook gives biology students an introduction to statistical practice all their own. It covers essential statistical topics with examples and exercises drawn from across the life sciences, including the fields of nursing, public health, and allied health. Based on David Moore’s The Basic Practice of Statistics, PSLS mirrors that #1 bestseller’s signature emphasis on statistical thinking, real data, and what statisticians actually do. The new edition includes new and updated exercises, examples, and samples of real data, as well as an expanded range of media tools for students and instructors.


Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications

Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications

Author: Wayne B. Nelson

Publisher: SIAM

Published: 2003-01-01

Total Pages: 157

ISBN-13: 0898715229

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Survival data consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. However, many applications involve repeated-events data, where a unit may accumulate numerous events over time. This applied book provides practitioners with basic nonparametric methods for such data.


Introductory Statistics for the Life and Biomedical Sciences

Introductory Statistics for the Life and Biomedical Sciences

Author: Julie Vu

Publisher:

Published: 2020-03

Total Pages:

ISBN-13: 9781943450114

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Introduction to Statistics for the Life and Biomedical Sciences has been written to be used in conjunction with a set of self-paced learning labs. These labs guide students through learning how to apply statistical ideas and concepts discussed in the text with the R computing language.The text discusses the important ideas used to support an interpretation (such as the notion of a confidence interval), rather than the process of generating such material from data (such as computing a confidence interval for a particular subset of individuals in a study). This allows students whose main focus is understanding statistical concepts to not be distracted by the details of a particular software package. In our experience, however, we have found that many students enter a research setting after only a single course in statistics. These students benefit from a practical introduction to data analysis that incorporates the use of a statistical computing language.In a classroom setting, we have found it beneficial for students to start working through the labs after having been exposed to the corresponding material in the text, either from self-reading or through an instructor presenting the main ideas. The labs are organized by chapter, and each lab corresponds to a particular section or set of sections in the text.There are traditional exercises at the end of each chapter that do not require the use of computing. In the current posting, Chapters 1 - 5 have end-of-chapter exercises. More complicated methods, such as multiple regression, do not lend themselves to hand calculation and computing is necessary for gaining practical experience with these methods. The lab exercises for these later chapters become an increasingly important part of mastering the material.An essential component of the learning labs are the "Lab Notes" accompanying each chapter. The lab notes are a detailed reference guide to the R functions that appear in the labs, written to be accessible to a first-time user of a computing language. They provide more explanation than available in the R help documentation, with examples specific to what is demonstrated in the labs.


Statistical Methods for Quality of Life Studies

Statistical Methods for Quality of Life Studies

Author: Mounir Mesbah

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 358

ISBN-13: 1475736258

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On October 16 and 17, 2000, we hosted an international workshop entitled "Statistical Design, Measurement, and Analysis of Health Related Quality of Life." The workshop was held in the beautiful city of Arradon, South Brittany, France with the main goal of fostering an interdisciplinary forum for discussion of theoretical and applied statistical issues arising in studies of health-related quality of life (HRQoL). Included were biostatisticians, psychometricians and public health professionals (e.g., physicians, sociologists, psychologists) active in the study ofHRQoL. In assembling this volume, we invited each conference participant to contribute a paper based on his or her presentation and the ensuing and very interesting discussions that took place in Arradon. All papers were peer-reviewed, by anonymous reviewers, and revised before final editing and acceptance. Although this process was quite time consuming, we believe that it greatly improved the volume as a whole, making this book a valuable contribution to the field ofHRQoL research. The volume presents a broad spectrum of papers presented at the Workshop, and thus illustrates the range of current research related to the theory, methods and applications of HRQoL, as well as the interdisciplinary nature ofthis work. Following an introduction written by Sir David Cox, it includes 27 articles organized into the following chapters.


Understanding Statistics and Experimental Design

Understanding Statistics and Experimental Design

Author: Michael H. Herzog

Publisher: Springer

Published: 2019-08-13

Total Pages: 146

ISBN-13: 3030034992

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This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.


OpenIntro Statistics

OpenIntro Statistics

Author: David Diez

Publisher:

Published: 2015-07-02

Total Pages:

ISBN-13: 9781943450046

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The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.


Statistical Research Methods in the Life Sciences

Statistical Research Methods in the Life Sciences

Author: Pejaver Vishwamber Rao

Publisher: Duxbury Resource Center

Published: 1998

Total Pages: 920

ISBN-13:

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Appropriate for all courses in statistical methods for the agricultural, life, health, and environmental sciences, this book offers a practical and modern approach that minimizes computation and emphasizes conceptual understanding. Rao continually emphasizes issues and topics most relevant to modern day research in the life sciences. For example, point and interval estimation take priority over testing of statistical hypothesis and methods and guidelines for determination of sample size are indicated whenever possible. Statistical Research Methods in the Life Sciences also presents a self-contained and complete discussion of each experimental situation considered. In the two-sample setting, for example, in addition to presenting the procedures under the usual analysis of variance assumption, Rao also presents methods for checking the validity of the assumptions.


Introduction to Statistical Data Analysis for the Life Sciences

Introduction to Statistical Data Analysis for the Life Sciences

Author: Claus Thorn Ekstrom

Publisher: CRC Press

Published: 2014-11-06

Total Pages: 526

ISBN-13: 1482238942

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A Hands-On Approach to Teaching Introductory StatisticsExpanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the m


Statistics for the Life Sciences

Statistics for the Life Sciences

Author: Myra L. Samuels

Publisher:

Published: 2012

Total Pages: 0

ISBN-13: 9780321652805

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Statistics for the Life Sciences, Fourth Edition, is the perfect book for introductory statistics classes, covering the key concepts of statistics as applied to the life sciences, while incorporating the tools and themes of modern data analysis. This text uses an abundance of real data in the exercises and examples to minimize computation, so that students can focus on the statistical concepts and issues, not the mathematics. Basic algebra is assumed as a prerequisite. ¿ This latest edition is also available as an enhanced Pearson eText. This exciting new version features an embedded versio.