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Statistics and Experimental Design: An Introduction for Biologists and Biochemists

TextbookOut of Print

By: GM Clarke

208 pages, Figs, tabs

Hodder Arnold

Paperback | Dec 1994 | Edition: 3 | #25957 | ISBN: 0340593245
Out of Print Details

About this book

Mathematically gentle introduction to experimental design emphasizing the principles and limitations of the standard statistical procedures.

The material is well written with clear notation and ample examples and exercises...A nice little book that can be highly recommeded for a non-mathematical introductory course in statistics for experimental scientists. -- Teaching Statistics, reviewing a previous edition should appeal to those wishing to learn statistical methods in an 'applied' way. It is easy to follow, gives an excellent grounding in statistical methods for the less mathematically inclined, and can be recommeded to biologists and to science students generally. -- Bias A book of this kind, addressed to a specialist audience judged mainly on the examples chosen to illustrate the procedures described and on the exercises set for the reader. Here the author has been very successful; he has drawn on a wide range of biological experiments. Particularly pleasing are those exercises which really make the reader think. -- Journal of Applied Bacteriology


Natural variation and types of data; studying and summarizing data graphically; numerical summaries of data; populations, samples and inferences; probability, the binomial and geometric distributions; randomness and the Poisson distribution; the normal distribution as a model for continuous data; significance tests for means - normal and student's t; confidence intervals for means; non-parametric tests for relocation; tests and estimates for variances; tests using the chi-squared distribution; correlation between two variable; fitting straight lines - linear regression; the principles of experimental design - the completely randomized design; randomized blocks and the precision of results; simple factorial experiments; missing observations and non-normality; a guide to choosing a significance test.

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