Data analysis methods in physical oceanography

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Data analysis methods in physical oceanography plus#
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Professional Ethics: Ethical issues in marine sciences are addressed throughout the program in both introductory and advanced courses, especially within the framework of the experience-based educational requirement.

Data analysis methods in physical oceanography plus#

All students in the School of Arts and Sciences must complete the SAS Core Requirements, plus the additional Major requirements below.

All students in the School of Environmental and Biological Sciences must complete the SEBS Core Requirements, plus the additional Major requirements below.

Students majoring in Marine Science must have a cumulative grade-point average of 2.0.

Students in SAS may also wish to consider the major in physics with the Ocean Physics option.

November 13: Alternatives to segmenting to compute spectra: averaging in frequency, spectra from the autocovariance.This option prepares students for graduate study in physical oceanography, meteorology, fluid dynamics, or a related field, as well as immediate employment in environmental agencies or consulting firms and technical positions in marine sciences.

November 4: More on windowing, and degrees of freedom, Homework #6 (due Wednesday, November 13).

October 30: More on error bars, normalization, and the sinc function.

October 28: Spectra, error bars on spectra, Homework #5 (due Monday, November 4).

October 23: Parseval's theorem and computing spectra.

October 21: Fourier transform notation, great traits of the Fourier transform, Homework #4.

October 16: Introducing the Fourier transform (chi-squared fitting, Nyquist frequency, cosine and sine transformations).

October 14: Least-squares fitting (linear fits, fitting sinusoids), Homework #3.

Meet at the entrance to the pier at 9:30 am. Note that the Shore Stations program would like to log their users via this form. Updated links to temperature and salinity data.

October 7: Probability density functions (error propagation, the central limit theorem, chi-squared distributions, evaluating whether data are drawn from different PDFs), Homework #2.

October 2: Probability density functions (common distributions, error analysis, outliers).

September 30: Introduction to the course (time series, mean, variance, standardДeviation, probability density functions), Homework #1.

Bia Villas Boas' github with python notebook versions of the notes.

Lecture notes and handouts: (See TritonED for slides, since they may contain

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Software packages, applications, routines Please take the time to submit an evaluation, since it provides valuable

Data analysis methods in physical oceanography how to#

Notification Affairs explaining how to evaluate this course. There will be some assigned reading (available inД®lectronic form), and students are expected to complete the reading.Д¬ourse evaluations (Nov 22-Dec 9): You should have received a To gain from this class, students are expected to come to class, participate inД¬lass discussions, ask questions. A draft write up will be dueДuring the final week of classes, and the final write up of your project will be due no later than The final problem set will be an independent project, which you will presentДuring the final exam time slot (Wednesday 11 December, 8:00-11:00). The standards of scientific publication and identify your collaborators.) A midtermДЄnd final problem must be completed independently. For most of the problem sets, you may workД¬ollaboratively, though the work that you submit must be your own. Monday and Wednesday: 9:30-10:50, Spiess Hall 330Дiscussion: Friday: 9:30-10:20ish, Spiess Hall 330 (starting October 4)Д¬omplete weekly problem sets.