Quantitative Foresight and Trend Analysis

Catalog description

Students learn rigorous, data-driven methods for exploring future possibilities across societal, technological, environmental and economic domains. The course blends foundational concepts in uncertainty, probability and forecasting with hands-on training in quantitative tools such as regression analysis, Bayesian inference, Monte Carlo simulations, operations research and system dynamics modeling. Students engage with trend analysis, scenario development and system modeling, learning to construct and interpret causal loop diagrams, stock-flow models and interactive simulations. Emphasizes applied learning: students use Vensim PLE, Excel/Google Sheets and Google Colab to develop models, analyze real-world data and effectively communicate findings. Through interdisciplinary modules, examines technoeconomic, environmental, health, social and political futures, integrating both quantitative methods and critical thinking to assess implications for policy, strategy and decision making.