Environmental Analysis Tools (ENEN90032)

AIMS

The aim of this subject is to help students develop capability to effectively summarise environmental variables met in the course of research and design, to select appropriate statistical models describing the data structure, and to conduct statistical inference on underlying processes. Students will apply a variety of models from a conventional or Bayesian approach to solve the problems at hand and derive deterministic or stochastic inferences from them.

The subject is composed of four wide-ranging topics from exploratory data analysis to spatial modelling. At the beginning of each topic, students are provided with a set of data from environmental research, and a number of analysis tools are conveyed in the lectures. The mathematical aspects of the subject build on concepts developed in fundamental engineering mathematics and statistics courses from undergraduate courses. It supports student learning in the capstone design and research projects where data analysis skills are assumed.

The subject provides a fundamental skill for a career in environmental engineering where the ability to analyse and communicate the meaning of time series and spatial data sets are expected.

INDICATIVE CONTENT

Specific topics include:

1. Exploratory Data Analysis

• Summary statistics and probability models
• Analysis of variability and hypothesis test
• Linear regression and verification/validation.

2. Time Series Analysis

• Introduction to multivariate analysis
• Principle component analysis
• Stochastic forecast and verification.

3. Methods for Multivariate Data

• Multivariate linear regression
• Principle component analysis.

4. Analysis of Spatial Data

• Simple spatial interpolations
• Analysis of spatial variability
• Spatial models and Kriging.