Week 11 Overview
| Dates | 31 March 2025 - 04 April 2025 |
| Reading | Required: SCIU4T4 Workbook chapter 34 |
| Recommended: None | |
| Suggested: None | |
| Advanced: Ernst (2004) (Download) | |
| Lectures | 11.1: Introduction to randomisation (18:43 min; Video) |
| 11.2: Assumptions of randomisation (11:03 min; Video) | |
| 11.3: Bootstrapping (11:43 min; Video) | |
| 11.4: Monte Carlo (min; Video) | |
| Lecture | Test Review: 02 APR 2025 (WED) 09:00-10:00 Cottrell LT B4 |
| Practical | Using R (Chapter 36) |
| Room: Cottrell 2A15 | |
| Group A: 02 APR 2025 (WED) 14:00-17:00 | |
| Group B: 03 APR 2025 (THU) 15:00-18:00 | |
| Help hours | Brad Duthie |
| Room: Cottrell 2Y8 | |
| 04 APR 2025 (FRI) 14:00-16:00 | |
| Assessments | Week 11 Practice quiz on Canvas |
| Test 2S on Canvas (02 APR 2025 at 11:00-13:00) |
Week 11 introduces randomisation approaches and the R programming language.
Chapter 35 takes a different approach to explaining hypothesis tests. Instead of specifying null distributions beforehand, we can use randomisation to build a null distribution from the sampled data. Randomisation is a flexible tool for hypothesis testing, but it also provides a different perspective on what p-values really are and how to think about them. Since hypothesis tests and, in particular, p-values are so often misunderstood, explaining how they work from this different perspective can be very instructive. For some students, randomisation is the topic in which the nature of p-values finally starts to become clear, and this is the primary motivation for including it in this book. Chapter 35 introduces randomisation as a tool for testing the same null hypothesis as the independent samples t-test, and compares the two approaches side by side to demonstrate their equivalence. It then introduces bootstrapping as a method for obtaining confidence intervals.
Chapter 36 Introduces the R programming language, which has become the most common and versatile tool for data analysis in the biological and environmental sciences. Jamovi was built on top of the R programming language. This chapter introduces the very basics of working in R.