Statistics Explained, An Introductory Guide for Life Scientists (Paperback)

Preface; 1. Introduction; 2. 'Doing Science' - hypotheses, experiments and disproof; 3. Collecting and displaying data; 4. Introductory concepts of experimental design; 5. Probability helps you make a decision about your results; 6. Working from samples - data, populations and statistics; 7. Normal distributions - test for comparing the means of one or two samples; 8. Type 1 and Type 2 error, power and sample size; 9. Single factor analysis of variance; 10. Multiple comparisons after ANOVA; 11. Two factor analysis of variance; 12. Important assumptions of analysis of variance: transformations and a test for equality of variances; 13. Two factor analysis of variance without replication, and nested analysis of variance; 14. Relationships between variables: linear correlation and linear regression; 15. Simple linear regression; 16. Non-parametric statistics; 17. Non-parametric tests for nominal scale data; 18. Non-parametric tests for ratio, interval or ordinal scale data; 19. Choosing a test; 20. Doing science responsibly and ethically.