Introduces data analysis methods regularly encountered within the ocean and earth sciences. Topics include: error propagation, least squares analysis, data interpolation methods, empirical orthogonal functions, and Monte Carlo methods applied to problems drawn from oceanographic and earth sciences datasets. Introduces and uses a high-level computing and visualization package of their choice (e.g., Matlab, python, R, Julia). Student project consists of analysis of the student's own dataset.
1 term
Other grades
University of California, Santa Cruz
OCEA 260 at UCSC: average GPA 3.67 across 10 students. Grade distribution by term. Introduces data analysis methods regularly encountered within the ocean and…
Average GPA: 3.67
Grade distribution records: 10 students across 1 terms.
| Grade | Students | Percent |
|---|---|---|
| A+ | 3 | 30.0% |
| A | 1 | 10.0% |
| A- | 1 | 10.0% |
| B | 2 | 20.0% |
| S | 3 | 30.0% |
Based on 10 student grade records across 1 term and 1 professor.
The course page is taking longer to load. This summary is still available.
We could not load the full course details. This summary is still available.
Still loading. This can take a moment on a slow connection.
Loading My Class Grades