Aims and Fit of Module

The aim of this module is to guide students in the theory and techniques of statistical data analysis in Environmental Sciences. Students learn how to apply and present statistical analyses such as: analysis of variance, Bayesian statistics, clustering, and regression analysis using various datasets.

Learning outcomes

A. understand the concepts of Analysis of Variance, Bayesian analysis, clustering analysis, and regression analysis and their applications in Environmental Sciences
B. demonstrate of ability to use statistical software to conduct statistical analyses
C. interpret environmental data by constructing regression models
D. present statistical results via appropriate graphs and tables both in presentations and in publications.

Method of teaching and learning

The module is delivered through a series of lectures and practical. The lectures provide statistical theories and case studies from different research areas in Environmental Sciences. The practical’s involve students in problem-oriented exercises, group work on case studies, discussions, and presentations. Students apply the knowledge learnt in the lectures and practical to the assignments. Feedback will be provided to students afterwards to improve their understanding in the use of statistical theories in Environmental Sciences.