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 website that provides all data sets, questions for each chapter and links to software

/pdf/experimental-design-and-data-analysis-for-biologists-8ybva8d53x.pdf

Experimental Design and Data Analysis for Biologists

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

A review is presented of the book “Heuristics and Biases: The Psychology of Intuitive Judgment,” edited by Thomas Gilovich, Dale Griffin, and Daniel Kahneman.

Heuristics and Biases: The Psychology of Intuitive Judgment

Much research in the last two decades has demon- strated that human responses deviate from the performance deemed normative according to various models of decision mak- ing and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be inter- preted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational limitations, (3) the wrong norm being applied by the experi- menter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implica- tions of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance er- rors are a minor factor in the gap; computational limitations un- derlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Un- expected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0140525X00003435

Individual differences in reasoning: Implications for the rationality debate?

Criticism and the Growth of Knowledge. Edited by I. Lakatos and A. Musgrave. Pp. viii, 282. £3·50, paperback £1. 1970. (Cambridge University Press.)

Preface Introduction 1. The Case for Materialism 2. Conceptual Dualism 3. The Impossibility of Zombies 4. Phenomenal Concepts 5. The Explanatory Gap 6. The Intuition of Distinctness 7. Prospects for the Scientific Study of Phenomenal Consciousness Appendix: The History of the Completeness of Physics

Thinking about Consciousness

Realism and anti-realism an argument for anti-realism of belief belief and representation the teleological theory of representation the possibility of error universal rationality naturalized epistemology naturalized realism inferential processes relativism, history and scepticism.

Reality and representation

Article (also printed in Wolff, J. & Stone, M. (eds.), "Proper Ambition of Science" (2000))

David Papineau

Papers

Thinking about Consciousness

Reality and representation

The Rise of Physicalism

Reality and Representation

Phenomenal and Perceptual Concepts