Overview
This course develops the principles and practice of experimental design for obtaining credible evidence about treatment effects. Topics include causal questions, experimental units, treatments, responses, controls, randomization, replication, blocking, blinding, treatment fidelity, preregistration, and sources of experimental error.
Students examine completely randomized, randomized block, matched-pairs, factorial, fractional-factorial, nested, split-plot, and repeated-measures designs, together with response-surface and optimization methods. Analytical work includes analysis of variance, contrasts, interaction effects, multiple comparisons, model assumptions, residual diagnostics, transformations, missing observations, outliers, and robust methods.
The course emphasizes the relationships among design choices, estimands, precision, bias, statistical power, sample-size requirements, and generalizability. Applied laboratories use statistical software and examples from agriculture, medicine, manufacturing, psychology, and environmental research. Ethical, operational, and practical constraints are integrated into the interpretation and communication of causal conclusions.
Learning Outcomes
- Formulate research aims as testable causal hypotheses, estimands, and statistical models.
- Select and justify efficient experimental designs for specified scientific and operational objectives.
- Implement randomization, blocking, replication, blinding, and treatment-allocation procedures.
- Determine sample-size requirements using considerations of effect size, variability, power, and practical constraints.
- Analyze treatment, interaction, and contrast effects using appropriate analysis-of-variance methods.
- Evaluate model assumptions through residual diagnostics, transformations, sensitivity analyses, and robust procedures.
- Interpret statistical and practical significance while distinguishing designed experiments from observational studies.
- Synthesize ethical, operational, reproducibility, and generalizability considerations in experimental plans.
- Communicate experimental findings, limitations, and causal conclusions responsibly using statistical software and clear technical reporting.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Lab | 2 hours | Weekly | All semester |
| Tutorial | 1 hour | Fortnightly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Design proposal and rationale | 15.00% |
| Quiz | Quizzes (5 × 2%) | 10.00% |
| Deliverable | Laboratory reports (5 × 3%) | 15.00% |
| Test | Randomization and analysis practical | 15.00% |
| Exam | Mid-semester examination | 15.00% |
| Exam | Final examination | 30.00% |
Teaching Staff & Programs
This course is delivered jointly by faculty from the participating programs listed below. In line with the Douchewater Way, the University of Sexology tailors core instruction directly to each cohort's specific discipline — adapting curriculum to program needs rather than forcing students into a one-size-fits-all model. Learn more about our approach at The Douchewater Way.