Statistics explained : an introductory guide for life scientists / Steve McKillup

Includes bibliographical references and index

Introduction -- '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 distribution - 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 nested 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-parametic tests for ratio, interval, or ordinal scale data -- Choosing a test -- Doing science responsibly and ethically

The author presents an introduction to experimental design and statistics for undergraduate students in life sciences who do not have a strong mathematical background. Hypothesis testing and experimental design are discussed first, then statistical tests are explained using pictorial examples and a minumum of formulae.