Need an account? Click here to sign up. Download Free PDF. Quinn and Michael J. Peter Petraitis. A short summary of this paper. Download Download PDF. Translate PDF. Journal of Experimental Marine Biology and Ecology — www. Quinn and Keough have written a wonderful book that is packed with lots of practical advice about statistical analyses.
Their goal was to strike a balance between how analyses are done versus how to use them correctly, and I think they have achieved that balance. Quinn and Keough cover all the standard material found in introductory books on univariate statistics and provide several chapters on multivariate methods. I found the 19 chapters well organized and informative. More technical information is covered in boxes outside of the main body of text and each chapter ends with a section of general issues and hints for analysis, which are short and listed with bullet points.
Data for the examples come from real experiments, and the raw data are available on the web as text and Excel files so the reader can run their data in his or her favourite statistical package. While Quinn and Keough suggest their target audience is biologists, nearly all of the examples are from population and community ecology.
The book begins with four chapters that introduce the scientific method, probability distributions, estimation, hypothesis testing and graphical exploration of data.
These chapters go well beyond the basics, and Quinn and Keough discuss a wide range of topic including Popperian falsification, maximum likelihood estimation, jackknife and bootstrap methods, Bayesian inference and hypothesis testing, decision errors, significance levels for multiple testing, meta-analysis and censored data.
The book closes with a wonderful chapter on presentation of results. The two chapters on regression cover linear and multiple regression, provide a discussion of diagnostics, transformations and stepwise methods and introduce a number of less well-known methods such as smoothing with splines and locally weighted regression i. And, just to top things off, there is a chapter on logistic regression and generalized linear models and a chapter on the analysis of frequencies.
Is it not obvious what is required ro pertorm an experiment? Isn't rhe scientific method well established, developed over hundreds of years of philosophical reasoning, and distilled into consistent sciemific practice?
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