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|a McKillup, Steve.
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|a Statistics explained :
|b an introductory guide for life sciences /
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|a Cambridge, UK ;
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|a Includes bibliographical references (pages 261-262) and index.
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|a 'Doing science'--hypotheses, experiments, and disproof -- Collecting and displaying data -- Introductory concepts of experimental design -- Probability helps you make a decision about your results -- Working from samples--data, populations, and statistics -- Normal distributions--tests for comparing the means of one and two samples -- Type 1 and type 2 errors, power, and sample size -- Single factor analysis of variance -- Multiple comparisons after ANOVA -- Two factor analysis of variance -- Important assumptions of analysis of variance: transformations and a test for equality of variances -- Two factor analysis of variance without replication, and nestedmil analysis of variance -- Relationships between variables: linear correlation and linear regression -- Simple linear regression -- Non-parametric statistics -- Non-parametric tests for nominal scale data -- Non-parametric tests for ratio, interval, or ordinal scale data -- Choosing a test -- Doing science responsibly and ethically.
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520 |
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|a Statistics Explained is a reader-friendly introduction to experimental design and statistics for undergraduate students in the life sciences, particularly those without a strong mathematical background. Topics are explained clearly and succinctly with minimum use of formulae and terminology, making this book essential reading for all bioscience undergraduates.
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|d Cambridge, UK ; New York : Cambridge University Press, 2005
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