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Introduction to Statistical Data Analysis for the Life Sciences, Second Edition, Ekstrom


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Цена: 9798.00р.
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Автор: Ekstrom
Название:  Introduction to Statistical Data Analysis for the Life Sciences, Second Edition
ISBN: 9781482238938
Издательство: Taylor&Francis
Классификация:

ISBN-10: 1482238934
Обложка/Формат: Paperback
Страницы: 526
Вес: 0.78 кг.
Дата издания: 18.12.2014
Язык: English
Издание: 2 ed
Иллюстрации: 97 tables, black and white; 101 illustrations, black and white
Размер: 157 x 235 x 22
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Epidemiology & medical statistics, MATHEMATICS / Probability & Statistics / General,MEDICAL / Biostatistics
Основная тема: Medical Statistics & Computing
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Европейский союз
Описание:

A Hands-On Approach to Teaching Introductory Statistics

Expanded 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 mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets.

New to the Second Edition

  • A new chapter on non-linear regression models
  • A new chapter that contains examples of complete data analyses, illustrating how a full-fledged statistical analysis is undertaken
  • Additional exercises in most chapters
  • A summary of statistical formulas related to the specific designs used to teach the statistical concepts

This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.




      Старое издание

Statistical Learning for Biomedical Data

Автор: Malley
Название: Statistical Learning for Biomedical Data
ISBN: 0521699096 ISBN-13(EAN): 9780521699099
Издательство: Cambridge Academ
Рейтинг:
Цена: 6494.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Biomedical researchers need machine learning techniques to make predictions such as survival/death or response to treatment when data sets are large and complex. This highly motivating introduction to these machines explains underlying principles in nontechnical language, using many examples and figures, and connects these new methods to familiar techniques.

An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
Рейтинг:
Цена: 27712.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition

Автор: Nicholas J. Horton , Ken Kleinman
Название: Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition
ISBN: 1482237369 ISBN-13(EAN): 9781482237368
Издательство: Taylor&Francis
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Цена: 11789.00 р.
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Описание:

Improve Your Analytical Skills

Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book's simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.

New to the Second Edition

  • The use of RStudio, which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflows
  • New chapter of case studies illustrating examples of useful data management tasks, reading complex files, making and annotating maps, "scraping" data from the web, mining text files, and generating dynamic graphics
  • New chapter on special topics that describes key features, such as processing by group, and explores important areas of statistics, including Bayesian methods, propensity scores, and bootstrapping
  • New chapter on simulation that includes examples of data generated from complex models and distributions
  • A detailed discussion of the philosophy and use of the knitr and markdown packages for R
  • New packages that extend the functionality of R and facilitate sophisticated analyses
  • Reorganized and enhanced chapters on data input and output, data management, statistical and mathematical functions, programming, high-level graphics plots, and the customization of plots

Easily Find Your Desired Task

Conveniently organized by short, clear descriptive entries, this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing, cross-referencing, and worked examples in the text. Datasets and code are available for download on a supplementary website.

Introduction to Statistical Analysis of Laboratory Data

Автор: Alfred Bartolucci, Karan P. Singh, Sejong Bae
Название: Introduction to Statistical Analysis of Laboratory Data
ISBN: 1118736869 ISBN-13(EAN): 9781118736869
Издательство: Wiley
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Цена: 16466.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis

  • Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process
  • Introduces terminology used in many applications such as the interpretation of assay design and validation as well as "fit for purpose" procedures including real world examples
  • Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities
  • Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation
  • Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions

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