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data analysis, programming, environmental science, public policy, economics


Key Points:

  • Impact assessment of regulations and/or human behaviors on the environment

  • Methods from environmental studies, data science, and economics

Detailed Description:

Recent advancements in computing and increased data accessibility have empowered researchers to establish connections between environmental factors and social outcomes. FIRE Sustainability Analytics employs techniques from economics, data science, and geography to comprehensively examine the socioeconomic impacts stemming from climate change and environmental regulations.


Key Points:

  • Various policies or actions can have intended and unintended consequences.

  • By analyzing data from the past, we can help inform future policymaking.

Detailed Description:

The degradation of the environment stands as one of humanity's most pressing challenges. Policies and actions can yield both intended and unintended consequences. By analyzing the effects of previous environmental events and regulations, we can provide valuable insights to guide policymakers in making more informed decisions for the future.


Key Points:

  • Interdisciplinary teamwork

  • Data literacy; ability to read, understand, create, and communicate data as information

  • Spatial and statistical analysis

  • Programming in R

  • Causal inference

Detailed Description:

The stream tailors R programming to students of all skill levels, ranging from those with basic skills to those seeking to apply it in cutting-edge applications. Every student learns how to program in R to perform tasks such as querying large datasets, cleaning and integrating environmental and socioeconomic data, creating data visualizations in the form of graphs and maps, and utilizing econometrics and machine learning techniques to estimate causal relationships.


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