- Class Number 4931
- Term Code 2930
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- AsPr David Heslop
- AsPr Michael Ellwood
- Class Dates
- Class Start Date 25/02/2019
- Class End Date 31/05/2019
- Census Date 31/03/2019
- Last Date to Enrol 04/03/2019
This course focuses on analytical methods and data science in Earth Sciences. It includes understanding types of instrumentation and other analytical techniques essential to the Earth Sciences, how to assess data quality, how to document and present results effectively, and how to use statistical and numerical techniques to interpret data quantitatively in Earth Sciences.
Upon successful completion, students will have the knowledge and skills to:
- Describe the theoretical and practical aspects of major analytical instrumentation (including electron microprobe, FTIR, XRF, XRD, mass spectrometery - ICPMS, TIMS, SIMS) used across the Earth Sciences in fields such as geochemistry, mineralogy, biogeochemistry, marine and climate science. The emphasis is on instrumentation and laboratories available to students at RSES.
- Evaluate the strengths and weaknesses of different analytical techniques for different applications.
- Appraise the advantages and disadvantages of different analytical techniques for a research program.
- Undertake data assessment and quality control.
- Explain the requirements for data documentation and reporting in a professional context.
- Assess a suite of relevant statistical techniques and use them to evaluate data sets to assess quality of data needed to obtain specific goals.
- Communicate effectively a variety of data science tools as applicable to Earth Science research problems.
This course will involve in-class problem solving and a range of interactive examples. Laboratory practicals will place a strong focus on "learning by doing".
In Week 1 there will be a short (approx. 4 hour) field trip to Lake Burley Griffin. Specific information will be provided in class and on the course Wattle page.
Additional Course Costs
A lab coat and safety glasses will be required for laboratory activities in Week 2. Closed-toe shoes are also compulsory when working in laboratories.
Bring a laptop to class if you have one. Please see Wattle for more information.
Weeks 4, 5 & 6 will require a laptop for interactive Python-based processing examples. We will access Python via the RSES server, so you don't need to install any specific software for this component of the course.
Weeks 4, 5 and 6 assume some very basic knowledge of maths and statistics. Introductory material is available on the course Wattle page, please review this before Week 4. A reading list will be provided with the course handout.
Students will be given feedback in the following forms in this course:
- written comments
- verbal comments
- feedback to whole class, groups, individuals, focus group etc
ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
|Week/Session||Summary of Activities||Assessment|
|1||Introduction and principles of analytical analysis and field sampling||Sampling Design Report|
|2||Preparation of samples for elemental analysis||Risk Assessment Report|
|3||Data reduction and report preparation||Data Reduction Report|
|4||Introduction to Data Science & Hypothesis Testing|
|5||Correlation and Regression & Error Analysis|
|6||Multivariate Statistics||Homework Assignment (covering Weeks 4, 5, 6)|
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Sampling Design Report||16 %||09/03/2019||23/03/2019||1, 2, 3|
|Risk Assessment Report||17 %||16/03/2019||30/03/2019||1, 2, 3|
|Data Reduction Report||17 %||23/03/2019||06/04/2019||4, 5, 6|
|Data Science Homework Assignment||50 %||25/05/2019||10/06/2019||1,2,3,4,5,6,7|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.
Moderation of Assessment
Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
Students are expected to participate actively in all components of the course.
Assessment Task 1
Learning Outcomes: 1, 2, 3
Sampling Design Report
This assessment will involve a written report (4-6 pages) outlining ideas fundamental to the design of sampling schemes in the Earth Sciences.
Assessment Task 2
Learning Outcomes: 1, 2, 3
Risk Assessment Report
This assessment will involve a written report (4-6 pages) that discusses aspects of risk when working in a laboratory and the formulation of risk assessment documents.
Assessment Task 3
Learning Outcomes: 4, 5, 6
Data Reduction Report
This assessment will involve a written report (4-6 pages) that outlines data synthesis approaches that can be applied to laboratory data sets.
Assessment Task 4
Learning Outcomes: 1,2,3,4,5,6,7
Data Science Homework Assignment
This is individual homework assignment that will involve processing a real data set using the techniques discussed in Weeks 4, 5 & 6 of the course. Your assignment should take the form of a Jupyter Notebook that contains both the code you developed to process the data and a Markdown-based explanation of the steps you took and techniques you used. This explanation is a key component of the assignment, which should be detailed and include, for example, the equations you used, a description of the terms included in them, etc.
Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.
You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.
For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.
Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:
- Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.
Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.
Assignment grades will be uploaded to Wattle by the date specified above. Students are encouraged to request specific feedback from the appropriate member of the teaching team.
Extensions and Penalties
Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.
Distribution of grades policy
Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.
Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.
Support for students
The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Paleomagnetism, Data Science
AsPr David Heslop