drawing-conclusions
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difuse-dartmouth / geography-extreme-climate-events
Students examine drought, famine, floods, landslides and other extreme weather events looking through the lens of climate change, while developing skills in Python’s Numpy and pandas.
Language:Jupyter Notebook 3Students learn the way astrophysicists manipulate observatory data and perform analyses in Google Colab Python notebooks with an emphasis on data visualization and plot interpretation.
Language:Jupyter Notebook 0This repo contains data and code for a web app designed for the visualization and analysis of geospatial data for the ENVS3 course, developed by the DIFUSE project (NSF IUSE-1917002).
Language:Jupyter Notebook 0Students explore and observe patterns from raw eddy covariance data and implications towards net ecosystem exchange. Students discover important meteorological and phenological properties that contribute towards the overall ecosystem.
0Students engage with the wind energy power equations and explore other considerations in the siting of a wind farm in a 3-part Google Colab Python notebook.
Language:Jupyter Notebook 0- earth-science-environmental-change
Students collect and analyze solar incidence angles over time to evaluate their own hypotheses, coupling this with the additional data analysis in Excel to draw conclusions about environmental change.
- engineering-glucose-model-ode
Students find numerical solutions to a first order ordinary differential equation (ODE) model of glucose-insulin system using Euler’s method and least squares in MATLAB.
- sociology-health-outcomes
Students examine the effect of different factors on self-rated health in Texas counties using interactive maps and regression analyses in Google Colab Python notebooks.