- Code EMSC4712
- Unit Value 6 units
- 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
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.
Upon successful completion, students will have the knowledge and skills to:
- 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;
- Analyse, design, and build practical circuits;
- Interpret and evaluate electronic circuit diagrams;
- Apply the basic principles of the design of electronic circuits to optimise signals to noise ratios in data acquisition systems;
- Understand and perform a suite of statistical techniques;
- Evaluate data sets using appropriate techniques;
- Assess quality of data needed to obtain specific goals;
- Apply effectively a variety of data analysis tools.
- Theory exam (25) [LO 5,6,7]
- Data Practicals (25) [LO 5,6,7,8]
- Electronics Labs (25) [LO 2,3,4]
- Oral reports (25) [LO 1,2,3]
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- 6 units
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|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|6571||24 Jul 2023||31 Jul 2023||31 Aug 2023||27 Oct 2023||In Person||N/A|