Mick Keough
人物简介:
Ecology. He has taught experimental design and analysis courses for a number of years and has provided advice on the design and analysis of sampling and experimental programs in ecology and environmental monitoring to a wide range of university and government scientists. Gerry Quinn is a co-author of Monitoring Ecological Impacts: Concepts and Practice in Flowing Waters, Cambridge University Press, 2002.
Michael Keough is a Reader in Zoology at the University of Melbourne. His research interests lie in marine ecology, environmental science, and conservation biology. He has extensive experience teaching experimental design and analysis courses at a number of universities. He has also provided advice on design and analysis for environmental monitoring to a wide range of environmental consultants, and state and federal governments in Australia. Michael Keough is a co-author of Monitoring Ecological Impacts: Concepts and Practice in Flowing Waters, Cambridge University Press, 2002.
Experimental Design and Data Analysis for Biologists书籍相关信息
- ISBN:9780521811286
- 作者:Gerry Quinn / Mick Keough
- 出版社:Cambridge University Press
- 出版时间:2002-1
- 页数:556
- 价格:$ 158.20
- 纸张:暂无纸张
- 装帧:Hardcover
- 开本:暂无开本
- 语言:暂无语言
- 适合人群:Researchers in the field of biology, students studying biology or biostatistics, data analysts working in life sciences, educators teaching experimental design and data analysis, and anyone interested in applying statistical methods to biological research
- TAG:data analysis / Biostatistics / statistical software / Scientific Methodology / Life Sciences / Biology Research / Experimental Design
- 豆瓣评分:暂无豆瓣评分
- 更新时间:2025-05-16 22:03:00
内容简介:
An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a web-site that provides all data sets, questions for each chapter and links to software.