Overview
This advanced course examines the use of data to support strategic, operational, and public-sector decision-making. Students develop methods for framing ambiguous organizational questions, defining analytical problems, identifying stakeholders, assessing data quality, and selecting appropriate descriptive, predictive, causal, forecasting, optimization, simulation, and decision-analytic techniques.
The course addresses key performance indicators, dashboards, scenario planning, cost-benefit analysis, expected value, sensitivity analysis, risk assessment, experimentation, A/B testing, and decision-making under uncertainty. Students evaluate the effects of assumptions, missing data, measurement error, bias, confounding, and model limitations on analytical conclusions.
Emphasis is placed on ethical and responsible data use, including privacy, fairness, transparency, governance, and accountability. Through case analyses, decision memos, visualizations, presentations, and an integrated project, students produce actionable and defensible recommendations for technical and nontechnical audiences.
Learning Outcomes
- Translate organizational, strategic, and policy questions into clearly specified analytical problems.
- Evaluate data quality, measurement validity, assumptions, missingness, bias, confounding, and model limitations in decision contexts.
- Select and justify appropriate statistical, predictive, causal, forecasting, optimization, simulation, and decision-analysis methods.
- Interpret statistical results, model outputs, uncertainty estimates, performance indicators, and sensitivity analyses accurately.
- Compare alternatives under uncertainty using expected value, cost-benefit analysis, risk assessment, scenario planning, and related decision frameworks.
- Construct effective dashboards, data visualizations, and executive narratives for technical and nontechnical audiences.
- Critique analytical recommendations for ethical, privacy, fairness, transparency, governance, and accountability considerations.
- Synthesize evidence from real or realistic datasets into an actionable, documented, and defensible course-of-action recommendation.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Workshop | 2 hours | Weekly | All semester |
| Lab | 2 hours | Fortnightly | All semester |
| Tutorial | 1 hour | Weekly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Case analyses (2 × 10%) | 20.00% |
| Deliverable | Decision memo | 15.00% |
| Deliverable | Dashboard and executive presentation | 20.00% |
| Capstone | Integrated decision analysis project | 35.00% |
| Attendance | Participation in workshops and tutorials | 10.00% |
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.
