12.805 Data Analysis in Physical Oceanography
Directed at making scientifically-sensible inferences from physical oceanography data (both observations and models). Introduces linear inverse methods, including regression, singular value decomposition, objective mapping, and data assimilation. Connects these methods to time series analysis, including Fourier methods, spectra, coherence, and filtering. Focuses on working with data in a computer laboratory setting. Emphasizes how statistical information can be used to improve experimental design. Gives some attention to the instruments and algorithms used to acquire the data.
This class has no prerequisites.
12.805 will be offered this semester (Spring 2019). It is instructed by G. Gebbie.
Lecture occurs at *TO BE ARRANGED in null.
This class counts for a total of 12 credits.
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