This lesson introduces the foundations of sound experimental design and the importance of rigor and reproducibility in experimentation. The goal of this lesson is to provide conceptual understanding, methods, and practice in planning and evaluating experiments. Lesson structure is informed by Teaching Experimental Design by Derek J. Fry.
Prerequisites
Learners need to be able to:
- install R packages and load libraries
- use a R function
| Setup | Download files required for the lesson | |
| 00:00 | 1. Introduction |
What is reproducibility?
What is replicability? Why are replicability and reproducibility important? |
| 00:15 | 2. Why we need better design |
Why does good experimental design matter?
What are some of the features of good experimental design? |
| 00:45 | 3. Common flaws |
What are some common features of poor experimental design?
What are some consequences of poor experimental design? |
| 01:20 | 4. Types of experiments |
How are hypotheses generated or tested?
What are my experimental units? |
| 01:20 | 5. Experimental designs |
What are my experimental units?
How will treatments be assigned? What are some types of experimental design? |
| 01:20 | 6. Factorial designs | |
| 01:20 | 7. Power calculation and sample size |
What role does the p-value (alpha) have in determining sample size for a study?
What is type 2 error, and how does it correspond to the p-value and power of a test? What factors should be considered when estimating sample size for a study? |
| 01:20 | 8. Planning an experiment |
What is the problem or research question(s) the study will address?
What are the sources of variability? What factors should be considered when determining sampling strategies? How will the data be analyzed? |
| 01:20 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
This lesson was funded by NIH grant R25GM123516 (Churchill) and The Jackson Laboratory Director's Innovation Fund (McClatchy & Churchill).