Experimental Design for Laboratory Biologists

1. Introduction: 1.1 What is reproducibility?; 1.2 The psychology of scientific discovery; 1.3 Are most published results wrong?; 1.4 Frequentist statistical interference; 1.5 Which statistics software to use?; 2. Key ideas in experimental design: 2.1 Learning versus confirming experiments; 2.2 The fundamental experimental design equation; 2.3 Randomisation; 2.4 Blocking; 2.5 Blinding; 2.6 Effect type: fixed versus random; 2.7 Factor arrangement: crossed versus nested; 2.8 Interactions between variables; 2.9 Sampling; 2.10 Use of controls; 2.11 Front-aligned versus end-aligned designs; 2.12 Heterogeneity and confounding; 3. Replication (what is 'N'?): 3.1 Biological units; 3.2 Experimental units; 3.3 Observational units; 3.4 Relationship between units; 3.5 How is the experimental unit defined in other disciplines?; 4. Analysis of common designs: 4.1 Preliminary concepts; 4.2 Background to the designs; 4.3 Completely randomised designs; 4.4 Randomised block designs; 4.5 Split-unit designs; 4.6 Repeated measures designs; 5. Planning for success: 5.1 Choosing a good outcome variable; 5.2 Power analysis and sample size calculations; 5.3 Optimal experimental designs (rules of thumb); 5.4 When to stop collecting data?; 5.5 Putting it all together; 5.6 How to get lucky; 5.7 The statistical analysis plan; 6. Exploratory data analysis: 6.1 Quality control checks; 6.2 Preprocessing; 6.3 Understanding the structure of the data; Appendix A. Introduction to R; Appendix B. Glossary.