Statistics Explained: An Introductory Guide for Life Scientists

Preface 1. Introduction 2. Doing science: hypotheses, experiments and disproof 3. Collecting and displaying data 4. Introductory concepts of experimental design 5. Doing science responsibly and ethically 6. Probability helps you make a decision about your results 7. Probability explained 8. Using the normal distribution to make statistical decisions 9. Comparing the means of one and two samples of normally distributed data 10. Type 1 and Type 2 error, power and sample size 11. Single factor analysis of variance 12. Multiple comparisons after ANOVA 13. Two-factor analysis of variance 14. Important assumptions of analysis of variance, transformations and a test for equality of variances 15. More complex ANOVA 16. Relationships between variables: correlation and regression 17. Regression 18. Analysis of covariance 19. Non-parametric statistics 20. Non-parametric tests for nominal scale data 21. Non-parametric tests for ratio, interval or ordinal scale data 22. Introductory concepts of multivariate analysis 23. Choosing a test Appendix: critical values of chi-square, t and F References Index.

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