STATS 7200C - Masters Project in Statistics C - Part 3
North Terrace Campus - Semester 1 - 2017
General Course Information
Course Code STATS 7200C Course Masters Project in Statistics C - Part 3 Coordinating Unit School of Mathematical Sciences Term Semester 1 Level Postgraduate Coursework Location/s North Terrace Campus Available for Study Abroad and Exchange Restrictions MMaSc students only
No information currently available.
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn successful completion of this course students will have
1. Demonstrated familiarity with research in an area of statistical.
2. Demonstrated skills in interpreting and critically evaluating literature related to a current area of research in statistics.
3. Demonstrated skills in communicating mathematical and/or statistical research to an audience, both in written form and orally.
4. Demonstrated an understanding of research methods in statistics.
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1,2 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
1,2,4 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
Required ResourcesResources are recommended on an individual basis by project supervisors.
Learning & Teaching Activities
Learning & Teaching ModesThe research project provides an introduction to research in statistics in an area chosen by the student from a range of projects offered by staff in the School of Mathematical Sciences. Students learn by a combination of reading research papers and monographs, discussing aspects of the research project with their supervisor and presenting their work both in oral form through a seminar presentation and in written form through a thesis. The thesis can take the form of (i) a critical review of a topic (ii) an analysis of data, a problem or application using existing techniques (iii) a detailed exposition of results from the literature (iv) extensions or generalizations of existing work.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.Workload
Weekly supervisory meetings (1 hour/week): 12 hours.
Weekly project work (12 hours/week): 144 hours.
Total: 156 hours.
Learning Activities SummaryThe Masters Project involves several stages:
1. Initial literature review and topic proposal. An outline of the research project must be lodged with the Postgraduate Coursework Coordinator at the beginning of Week 7 of the student's first semester. Attendance at non-assessed Research Methodologies seminar.
2. Ongoing literature review and research. Planning of thesis and drafting of initial chapters. Students are expected to commence writing their thesis no later than the beginning of their second semester.
3. Research seminar held in the mid-semester break of the student's second semester.
4. Completion of thesis writing: students are expected to provide a complete thesis draft to their supervisor at the beginning of Week 9 of the student's second semester. The thesis is due on Friday of Week 12 of the student's second semester; it is lodged with the Postgraduate Coursework Coordinator.
The specifics of each of these stages is highly dependent on the nature of the project; they should be discussed with the project supervisor.
Small Group Discovery ExperienceThe research project typically involves the student and one or possibly two academic staff members.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment SummaryThe Masters Project has two main assessment components:
1. Research Seminar (worth 10% of the final grade).
2. Thesis (worth 90% of the final grade).
These assessment components determine the grade for STATS 7200D - Masters Project in Statistics D - Part 4 (the courses STATS 7200A, STATS 7200B and STATS 7200C have grades of CN associated with them).
Assessment Related RequirementsAn aggregate score of at least 50% is required to pass the Masters Project in Statistics D (the three courses Masters Project in Statistics A, B and C each receive a grade of CN).
Assessment DetailThe Masters Project is assessed on the basis of the Research Seminar (worth 10% of the final grade) and the Thesis (worth 90% of the final grade). The Research Seminar is assessed by a small committee comprising of academic staff, normally from each of the three disciplines (Applied, Pure and Statistics). The Thesis is assessed by two examiners from the School of Mathematical Sciences.
No information currently available.
Grades for your performance in this course will be awarded in accordance with the following scheme:
NOG (No Grade Associated) Grade Description CN Continuing
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
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