Schedule, syllabus and examination date

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Course content

Geophysical Data Science provides a foundation for statistical analysis and modeling of Earth System data sets. Students are initially provided a review of core fundamental statistical concepts: probability, distribution, linear and multiple regression. Through the semester, course material will advance to cover important tools in climate, earth system modeling, and hydrologic analysis, including: hypothesis testing and uncertainty analysis, stochastic processes, temporal and frequency domain analysis, principal component analysis and canonical correlation.

Learning outcome

After completing this course you will:

  • Have competence to manage, conduct quality control, and analyze and classify time series of complex geophysical data.
  • Be able to statistically characterize and model geophysical data.
  • Conduct analysis of extreme events in the temporal and frequency domain.
  • Conduct multiple linear regression.
  • Evaluate spatio-temporal variability.
  • Develop stochastic models and evaluate residuals from geophysical data.
  • Conduct basic time series analysis.
  • Perfrom basic kriging operations on spatial data.
  • Gain skills to manage large and complex data from earth system models, reanalysis datasets, satellite products, and heterogeneous observations.
  • Conduct an intensive data analysis project on own data.

Admission

PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.

If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.

PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.

Prerequisites

Recommended previous knowledge

  • Bachelor courses in basic mathematics, statistics and hydrology/meteorology/climatology/physical geography.

Overlapping courses

Teaching

Lectures 2 x 2 hours per week. Computer lab 3 hours weekly providing data-processing and practical programming exercises. Compulsory assignments and the intensive data analysis project are graded and must be approved before the final written exam.

Attendance at the first lecture is compulsory. Students who fail to meet, are considered to have withdrawn from the course unless they have previously given notice to the Study administration, email address: studieinfo@geo.uio.no

 

Examination

  • Exercises, assignments and the data analysis project are examined and counts together for 50%.
  • Final written examination (3 hours) counts for 50%.

Language of examination

The examination text is given in English, and you submit your response in English.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

Explanations and appeals

Resit an examination

Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.

Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.

Withdrawal from an examination

It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.

It will also be counted as one of the three attempts to sit the exam for this course, if you sit the exam for one of the following courses: GEO4310 – Stochastic methods in hydrology (continued), GEO9310, GEO4300 – Geophysical Data Science

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.

Evaluation

The course is subject to continuous evaluation. At regular intervals we also ask students to participate in a more comprehensive evaluation.

Facts about this course

Credits

10

Level

PhD

Teaching

Every autumn

Examination

Every autumn

Teaching language

English