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Statistics for the Biological Sciences Books

You are currently browsing 11–20 of 163 new and published books in the subject of Statistics for the Biological Sciences — sorted by publish date from newer books to older books.

For books that are not yet published; please browse forthcoming books.

New and Published Books – Page 2

  1. Statistical Inference

    An Integrated Approach, Second Edition

    By Helio S. Migon, Dani Gamerman, Francisco Louzada

    Series: Chapman & Hall/CRC Texts in Statistical Science

    A Balanced Treatment of Bayesian and Frequentist Inference Statistical Inference: An Integrated Approach, Second Edition presents an account of the Bayesian and frequentist approaches to statistical inference. Now with an additional author, this second edition places a more balanced emphasis on...

    Published September 3rd 2014 by Chapman and Hall/CRC

  2. Statistical Methods in Biology

    Design and Analysis of Experiments and Regression

    By S.J. Welham, S.A. Gezan, S.J. Clark, A. Mead

    Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas...

    Published August 22nd 2014 by Chapman and Hall/CRC

  3. Stated Preference Methods Using R

    By Hideo Aizaki, Tomoaki Nakatani, Kazuo Sato

    Series: Chapman & Hall/CRC The R Series

    Stated Preference Methods Using R explains how to use stated preference (SP) methods, which are a family of survey methods, to measure people’s preferences based on decision making in hypothetical choice situations. Along with giving introductory explanations of the methods, the book collates...

    Published August 15th 2014 by Chapman and Hall/CRC

  4. A Handbook of Statistical Graphics Using SAS ODS

    By Geoff Der, Brian S. Everitt

    Easily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they...

    Published August 15th 2014 by Chapman and Hall/CRC

  5. Analysis of Categorical Data with R

    By Christopher R. Bilder, Thomas M. Loughin

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Learn How to Properly Analyze Categorical DataAnalysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses...

    Published August 11th 2014 by Chapman and Hall/CRC

  6. Analysis of Capture-Recapture Data

    By Rachel S. McCrea, Byron J. T. Morgan

    Series: Chapman & Hall/CRC Interdisciplinary Statistics

    An important first step in studying the demography of wild animals is to identify the animals uniquely through applying markings, such as rings, tags, and bands. Once the animals are encountered again, researchers can study different forms of capture-recapture data to estimate features, such as the...

    Published August 1st 2014 by Chapman and Hall/CRC

  7. Linear Mixed Models

    A Practical Guide Using Statistical Software, Second Edition

    By Brady T. West, Kathleen B. Welch, Andrzej T Galecki

    Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues...

    Published July 17th 2014 by Chapman and Hall/CRC

  8. SAS and R

    Data Management, Statistical Analysis, and Graphics, Second Edition

    By Ken Kleinman, Nicholas J. Horton

    An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis,...

    Published July 17th 2014 by Chapman and Hall/CRC

  9. Linear Models with R, Second Edition

    By Julian J. Faraway

    Series: Chapman & Hall/CRC Texts in Statistical Science

    A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with...

    Published July 1st 2014 by Chapman and Hall/CRC

  10. A Handbook of Statistical Analyses using R, Third Edition

    By Torsten Hothorn, Brian S. Everitt

    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...

    Published June 25th 2014 by Chapman and Hall/CRC