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Statistics for biologists

"Introduces the principles of statistics concentrating on the underlying reasoning rather than on mathematical development or detailed instruction in technique. Emphasis is placed on developing a sound logical basis for quantitative inference and experimental design in practical biological problems"--Publisher description.

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  • ""Introduces the principles of statistics concentrating on the underlying reasoning rather than on mathematical development or detailed instruction in technique. Emphasis is placed on developing a sound logical basis for quantitative inference and experimental design in practical biological problems"--Publisher description."@en
  • "Problems, data, questions; Probability and other definitions; Combining probabilities; Significance, binomials, and X2; Continuous variates; Inference on means: the normal distribution; Unknown variance: the t-distribution; Design of experiments; Comparisons between means; Additional topics."
  • "This book has grown from nine hours oflectures, and about the same time in tutorial classes, that attempt to give first-year students of biology some understanding of statistics. I am convinced that such a short course should not be mathematical (though it can employ basic mathematical symbolism), and that it should give students an appreciation of statistical argument, even though this limits the amount of detailed instruction in techniques of analysis that can be included. A statistical cookery book would have been easier to write and much easier to read, but lacking in true educational content. I am more concerned to show 'why' than to present methods and rules. A further constraint, that of remaining within a reasonable price range, prevents reiteration of explanations: the reader is expected to remember what he has read, for he will not find standard terms and ideas explained afresh on each occasion of use. Many books that introduce statistics to biologists blur distinctions and evade logical issues, for example by failing to emphasize the distinction between a parameter and an estimator from a sample or by neglecting the role of randomization. On this, I aim to be un compromisingly correct - at least until reviewers point out my errors - but to do so through realistic examples rather than abstract symbolism."

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  • "Electronic books"

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  • "Statistics for biologists"@en
  • "Statistics for biologists"
  • "Statistics for Biologists"

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