4210. Data Science for Decision Making in Applied and Resource Economics
3.00 credits
Prerequisites: Recommended preparation: Statistics, such as STAT 1000Q or STAT 1100Q or a similar course. Not open for credit to students who have passed ARE 5210.
Grading Basis: Graded
This course introduces data science and its transformative role in decision-making across business and policy applications in applied and resource economics. Students will learn to analyze and interpret data using R, with hands-on practice in visualization, A/B testing, regression analysis, and machine learning. Designed for beginners, it emphasizes intuitive approaches and practical applications, preparing students to apply data science in real-world contexts.
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