Earth And Environmental Sciences · Columbia University
This class is part of the Climate & Society masters program. I strongly discourage DEES undergrads from taking it. This course is essentially remedial statistics and the amount of material taught is laughable for a 4 credit course. Tony teaches very simple statistics during the first half of the class and then Mingfang teaches decision-making models and supervises the final project. Tony is very nice but he sets the bar too low. Statistics is listed as a prerequisite which must be some sort of joke. We spent the first few weeks learning how to calculate the mean and determine the probability of getting heads when you flip a coin. Too much class time was dedicated to testing (4 class period + lab in total). Spending three entire class periods to see if we could copy stat practice problems was a waste of time. The midterm did not test whether we truly understood the statistical methods we had learned. It was open computer which was ridiculous as it not only allowed for, but facilitated cheating. The group decision-making projects were valuable, but the presentations took more than 5 hours because each group got 25 minutes to present. It was unreasonable to make everyone stay so long. Expectations for the projects weren't made clear. To summarize: very easy A, but avoid if you want to learn anything useful or be challenged. Fortunately the lecture notes are posted so you don't ha…
Ocean circulation and other mechanisms of climate systems
I learned how to do some basic coding in R, which is not a skill that I hoped to get out of this program, but still kind of cool nonetheless.
3 full class quizzes, open note/open computer (25%), 4+ hour stat midterm (25%), lab every week (you don't have to produce a formal lab write up, just answer questions) (25%), group project + individual final report (25%)
I learned about how the ocean and atmosphere interact to create climate systems, how ocean circulation works, and the carbon cycle.
I learned a lot about how statistics can be misleading & how to perform crop output functions that take into account internal variability. These skills can be used for climate models!
The foundation of earth's climate system
I learned statistics and decision modeling in regards to climate decisions
It is hard for me to recall what I learned in this course because of the volume of material. I feel that the course lost big picture and instead focused on minutia that was rarely related to the big picture.
quantitive climate data analysis and applications