Data Reasoning and Decision-Making

This course explores the principles and practices of data-driven decision-making, grounded in foundational statistics and quantitative reasoning. Students will examine how knowledge is validated, distinguishing credible and relevant methods of assembling and interpreting quantitative information. The course covers the definitions and distinctions between inputs, outputs, and outcomes, the use of logic models, and the necessary data infrastructure for effective practices. Additionally, students will learn to use data to justify and support change initiatives, linking data-driven insights to change management strategies. Engaging with case studies, real-world applications, and emerging trends, students will develop critical thinking and quantitative reasoning skills to address complexities and uncertainties in decision-making processes that are heavily informed by data.