Data Analysis

David Heslop

https://earthsciences.anu.edu.au/people/academics/dr-david-heslop#acton-tabs-link--tabs-person_tabs-middle-1

Australian National University
Author Profile

Summary

The aim of this course is to provide an introduction to statistical and numerical techniques that are useful in the analysis and characterization of geological data. A focus is placed on conceptual understanding of how specific methods work and the situations in which they can and cannot be applied. A number of practical examples are discussed during the course, providing the opportunity for hands-on learning through the processing of real data sets using MATLAB. The experience gained in this course should help students approach their own research problems.

MATLAB allows students to perform all steps of a data analysis sequencing including the production of high quality graphics. Most students have limited programming experience and I've found MATLAB to more intuitable for beginners compared to languages such as R or Python.


Course URL: http://programsandcourses.anu.edu.au/course/EMSC8023
Course Size:
15-30

Course Format:
Integrated lecture and lab

Institution Type:
University with graduate programs, including doctoral programs

Course Context:

This is a compulsory postgraduate course aimed to provide students with an introduction to the data analysis tools they will need to undertake their own research projects. The course has no prerequisites and therefore no prior knowledge of statistics or data analysis is assumed. The level of mathematics is kept to a minimum in order that students from various backgrounds will find the course useful.

Course Content:

The Data Analysis course aims to provide geoscience students with an understanding and ability to perform a suite of statistical techniques. This includes demonstrating techniques that are appropriate to the analysis of different earth science data sets and assessing the quality of data needed to obtain specific goals. MATLAB is used as part of interactive examples, which are designed to demonstrate the various computational steps involved in a given technique.

Course Goals:

  • Students should understand and be able to perform a suite of statistical techniques.
  • Students should be able to evaluate earth science different data sets using appropriate techniques.
  • Students should be able to assess the quality of data needed to obtain specific goals.
  • Students should be able to communicate effectively in order to discuss the use of data analysis tools in the context of earth science research problems.

Course Features:

This is a week long course that consists of lectures and interactive examples. The majority of students have limited experience in data processing, therefore it is essential to demonstrate how this course is relevant to their own research problems. To achieve this goal much of the lecture content is delivered in a discussion-style, which is designed to help the students understand new concepts and appreciate their applicability. The course is separated into a collection of interlinked topics and interactive examples (using step-by-step MATLAB code) to help the students appreciate how a given technique can be implemented.

Course Philosophy:

I developed the course design based on my own teaching experience. The use of numerous embedded interactive examples helps to break-up the lecture content and keeps the students engaged. Many of the students do not have a strong background in mathematics, so it is important to focus on concepts rather than the underlying theory. By using MATLAB the students can see that a powerful analysis tool is available to them, which (with some investment of effort) will increase their own research productivity.

Assessment:

A 1 day practical assessment where students have to process and interpret a real data set using MATLAB. They have a number of defined tasks to perform and then deliver their results to the class in a 15 minute presentation (with questions). This presentation forms the basis of their final grade.

Syllabus:

Teaching Materials:

Data Analysis course handout (Acrobat (PDF) 9.9MB Oct15 15)

References and Notes: