After the completion of the course, the student should be able to
identify statistical methods that can be used to handle large amounts of earth science data
use statistical tools for modelling and analysis within the environmental sciences
carry out time-series analyses on climatological and hydrological data sets
compute return times for extreme events such as peak flows
Shapes of probability density functions including measures of central tendency, dispersion and symmetry. Expectation and estimation. Discrete and continuous probability distributions, especially normal and extreme-value distributions. Frequency and spectral analysis of climatological and hydrological measurement series. Confidence intervals and hypothesis testing. Correlation, simple and multiple regression on earth science-related data. Variance analysis. Principal component analysis. Parameter-value estimation. Time-series analysis and simple stochastic models in physical geography and hydrology. Error theory.
Lectures, exercises, project work.
Assessment is divided among a written exam (3 credits) and exercises as well as the oral and written presentation of project reports (2 credits)