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Quantitative Analysis of Ocean Data


Course Description

This course familiarizes students with fundamental techniques and tools for oceanographic data analysis. It covers techniques including basic statistics, regression, time series, and spatial analysis, and tools needed to process and acquire ocean data, including general programming skills and use of data repositories.

Additional Requirements for Graduate Students:
Graduate students will be expected to do an in depth data analysis project, ideally related to their research topic to provide more real-world data analysis experience.


Athena Title

Quant Analysis Ocean Data


Undergraduate Pre or Corequisite

(MATH 2260 or MATH 2260E) and (MARS 3200 or MARS 4100/6100 or MARS 4200/6200)


Semester Course Offered

Offered fall


Grading System

A - F (Traditional)


Course Objectives

This course teaches students the practical use of essential data analysis techniques and tools for ocean data. Students are expected to: 1. Demonstrate familiarity with data analysis techniques, including basic statistics, regression, time series analysis, and spatial analysis. 2. Be able to apply those techniques to analyze a given ocean data set, selecting the correct statistical tools, and making good statistical inferences from their analysis. 3. Make use of a programming language and software tools to conduct their analyses. 4. Be able to find, download, and use ocean data from online oceanographic data repositories. Additional Requirements for Graduate Students: Graduate students will be expected to do an in depth data analysis project, ideally related to their research topic to provide more read-world data analysis experience.


Topical Outline

Introductory Statistics Distributions Sampling Tests (t-test, ANOVA, etc) Data Transformations Regression Analysis Linear Regression Non-linear Regression Curve-Fitting Time Series Analysis Data Filtering Cross- and Auto-correlation Fundamentals of Spectral Analysis Spatial Analysis Data Smoothing and Filtering Spatial Correlation Empirical Orthogonal Functions Programming Variables, Data Types Flow Control Functions Files, Parsing Packages/Libraries Data Repositories NOAA World Ocean Database NSF BCO-DMO NASA EODIS


Syllabus


Public CV