Quinn, G. P. creator Keough, Michael J. text uk United Kingdom Cambridge University 2024 2024 Second edition. monographic eng

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xix,387 p.; ill., 28cm -- 1.1 Almost every biological theory or hypothesis is a model of how nature works.<br/> -- 1.2 We use data to separate wrong models from (possibly) correct ones (or bad models from less bad ones).<br/> -- 1.3 There are many ways to reach wrong conclusions!<br/> -- 1.4 There are also many ways to be right!<br/> -- 1.5 Our philosophy in this books.<br/> -- 1.6 How this book is structured.<br/> -- 1.7 A bit of housekeeping. 1. Introduction.<br/> -- 2.1 Samples, population, and statistical inference.<br/> -- 2.2 Probability.<br/> -- 2.3 Probability distributions.<br/> -- 2.4 Frequentist ("classical") estimation.<br/> -- 2.5 Hypothesis testing.<br/> -- 2.6 Comments on frequentist inference.<br/> -- 2.7 Bayesian statistical inference. 2. Things to Know Before Proceeding.<br/> -- 3.1 Sampling design.<br/> -- 3.2 Experimental design.<br/> -- 3.3 Sample size for detecting differences: power analysis.<br/> -- 3.4 Key points. 3. Sampling and Experimental Design.<br/> Gerry P. Quinn, Victoria, Michael J. Keough, Revised edition of: Experimental design and data analysis for biologists / Gerry P. Quinn, Michael J. Keough. 2002. Includes bibliographical references. Biometry 570.151 QUE 9781107687677 260827 20260827132220.0