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A Handbook of Statistical Analyses using R, Third Edition, Hothorn


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Автор: Hothorn
Название:  A Handbook of Statistical Analyses using R, Third Edition
ISBN: 9781482204582
Издательство: Taylor&Francis
Классификация:

ISBN-10: 1482204584
Обложка/Формат: Paperback
Страницы: 456
Вес: 0.65 кг.
Дата издания: 14.08.2014
Язык: English
Издание: 3 ed
Иллюстрации: 78 tables, black and white; 153 illustrations, black and white
Размер: 235 x 156 x 21
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Biology, life sciences, MATHEMATICS / Probability & Statistics / General
Основная тема: Statistics for the Biological Sciences
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.

New to the Third Edition

  • Three new chapters on quantile regression, missing values, and Bayesian inference
  • Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables
  • Additional exercises
  • More detailed explanations of R code
  • New section in each chapter summarizing the results of the analyses
  • Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses

Whether youre a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.



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ISBN: 0071122214 ISBN-13(EAN): 9780071122214
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Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

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Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 184750.00 T
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Автор: Myers, Jerome L
Название: Research design and statistical analysis
ISBN: 0805864318 ISBN-13(EAN): 9780805864311
Издательство: Taylor&Francis
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Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
Рейтинг:
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Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

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Название: Agricultural Statistical Data Analysis Using Stata
ISBN: 1466585854 ISBN-13(EAN): 9781466585850
Издательство: Taylor&Francis
Рейтинг:
Цена: 84710.00 T
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Описание:

Practical statistics is a powerful tool used frequently by agricultural researchers and graduate students involved in investigating experimental design and analysis. One of the most widely used statistical analysis software packages for this purpose is Stata. The Stata software program has matured into a user-friendly environment with a wide variety of statistical functions. Agricultural Statistical Data Analysis Using Stata introduces readers to the use of Stata to solve agricultural statistical problems.

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Many agricultural researchers are unprepared for the statistics they will need to use in their profession. Written in an easy-to-read format with screen shots and illustrations, the book is suitable for a wide audience, including beginners in statistics who are new to Stata, as well as more advanced Stata users and those interested in more complex designs.


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Название: Essentials of Excel, Excel VBA, SAS and MINITAB for Statistical and Financial Analyses
ISBN: 3319388657 ISBN-13(EAN): 9783319388656
Издательство: Springer
Рейтинг:
Цена: 83850.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, Minitab, and SAS. Every chapter in this textbook engages the reader with data of individual stock, stock indices, options, and futures.One studies and uses statistics to learn how to study, analyze, and understand a data set of particular interest. Some of the more popular statistical programs that have been developed to use statistical and computational methods to analyze data sets are SAS, SPSS, and Minitab. Of those, we look at Minitab and SAS in this textbook. One of the main reasons to use Minitab is that it is the easiest to use among the popular statistical programs. We look at SAS because it is the leading statistical package used in industry. We also utilize the much less costly and ubiquitous Microsoft Excel to do statistical analysis, as the benefits of Excel have become widely recognized in the academic world and its analytical capabilities extend to about 90 percent of statistical analysis done in the business world. We demonstrate much of our statistical analysis using Excel and double check the analysis and outcomes using Minitab and SAS—also helpful in some analytical methods not possible or practical to do in Excel.


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