• Offered by Research School of Earth Sciences
  • ANU College ANU Joint Colleges of Science
  • Course subject Earth and Marine Science
  • Areas of interest Earth and Marine Sciences, Statistics, Astronomy and Astrophysics, Physics, Electronics
  • Academic career UGRD
  • Course convener
    • Prof Malcolm Sambridge
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Second Semester 2020
    See Future Offerings

This course includes an on campus activity/ies. Check timetable for details. Contact course convener if you are unable to travel to Canberra.

The proper analysis of scientific data is the most powerful tool we have for separating scientific fact from fiction, and a key part of the process in the modern practice of science is getting the data into an electronic format. This class will provide an introduction to the electronics methods and techniques most useful in instrumentation and laboratory settings, along with an introduction to statistical and numerical techniques that are useful in the analysis and characterisation of data. Students will have the opportunity to learn and practice the methods of signal conditioning, analog to digital conversion (and the reverse), and low-noise circuit design that are key to the high-fidelity transformation of signals into data. When analysing data, a focus will be 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 will be discussed during the course, providing the opportunity for hands-on learning through the processing of real data sets with statistical software and data evaluation programs. The experience gained in this course will help students approach their own research problems.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Understand of the principles of linear circuits, amplification and feedback, analog to digital conversion, digital to analog conversion, and the requirements of analog electronics to successfully interface with digital systems;
  2. Analyse, design, and build practical circuits;
  3. Interpret and evaluate electronic circuit diagrams;
  4. Apply the basic principles of the design of electronic circuits to optimise signals to noise ratios in data acquisition systems;
  5. Understand and perform a suite of statistical techniques;
  6. Evaluate data sets using appropriate techniques;
  7. Assess quality of data needed to obtain specific goals;
  8. Apply effectively a variety of data analysis tools.

Indicative Assessment

  1. Theory exam (25) [LO 5,6,7]
  2. Data Practicals (25) [LO 5,6,7,8]
  3. Electronics Labs (25) [LO 2,3,4]
  4. Oral reports (25) [LO 1,2,3]

In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle. 

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Inherent Requirements

Not yet determined

Prescribed Texts



Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

6.00 0.12500
Domestic fee paying students
Year Fee
2020 $4050
International fee paying students
Year Fee
2020 $5760
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
9726 27 Jul 2020 03 Aug 2020 31 Aug 2020 30 Oct 2020 In Person View

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