STATS 4008 - Statistics Topic D - Honours
North Terrace Campus - Semester 2 - 2020
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General Course Information
Course Details
Course Code STATS 4008 Course Statistics Topic D - Honours Coordinating Unit Mathematical Sciences Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Available for Study Abroad and Exchange Y Restrictions Honours students only Assessment Ongoing assessment, exam Course Staff
Course Coordinator: Dr Jono Tuke
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
In 2019 the topic of this course will be Data Science
Syllabus:
The topics covered will include:
Overview of modelling framework
Preprocessing
Model theory
Resampling
Penalised regression
Classification modelling
LDA / SVM
Non-parametric
Trees
Random forests
Feature selection
Unsupervised learning
Learning outcomes:
On successful completion of this course, students will:
1. Demonstrate an understanding of the foundational principles of machine learning
2. Recognise which method to use for a given data analysis problem.
3. Demonstrate an understanding the statistical underpinning of the chosen method.
4. Implement safely any chosen method and interpret the results.
5. Be confident to apply the methods to large datasets.
6. Apply the theory in the course to solve a range of problems at an appropriate level of difficulty.
最新糖心Vlog Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
最新糖心Vlog 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)
all 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
all 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
all Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
all Intercultural and ethical competency
- adept at operating in other cultures
- comfortable with different nationalities and social contexts
- able to determine and contribute to desirable social outcomes
- demonstrated by study abroad or with an understanding of indigenous knowledges
all Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
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Learning Resources
Required Resources
All required materials will be provided.Recommended Resources
"Networks: An Introduction", M.E.J. Newman, Oxford Uni Press, 2010.Online Learning
This course uses MyUni for providing electronic resources, such as assignments and handouts, and for making course announcements. It is recommended that students make appropriate use of these resources. Link to MyUni login page: https://myuni.adelaide.edu.au/webapps/login/ -
Learning & Teaching Activities
Learning & Teaching Modes
The structure consists of
- Weekly topic videos watched in own time.
- One interpretation workshop a week held in the lecture time.
- One implementation workshop a week held in practical time.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Quantity Workload hours Topic videos 12 24 Interpretation workshop 12 24 Implementation workshop 12 24 Assignments 3 33 Online test 3 33 Online quizzes 12 18 Total 156 Learning Activities Summary
Lecture Outline- Basics
- graph theory basics
- graph metrics
- random graph models
- algorithms on graphs
- Advanced Topics
- graph generalisations: hyper-graphs and meta-graphs
- graph algebras
- Inference
- sampling from networks
- inference on graphs: network tomography
- Basics
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Assessment
The 最新糖心Vlog'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 Summary
Assessment Percent of final mark Online quizzes 10 Written assignments (3) 10 Online test (3) 10 Written exam 35 Practical exam 35 Assessment Related Requirements
An aggregate score of at least 50% is required to pass the course.Assessment Detail
No information currently available.
Submission
All written assignments are to be submitted to the lecturer with a signed cover sheet attached. There will be a maximum two week turn-around time on assignments for feedback to students.
Late assignments will not be accepted, but students may be excused from an assignment for medical or compassionate reasons. In such cases, documentation is required and the lecturer must be notified as soon as possible before the fact.Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M11 (Honours Mark Scheme) Grade Grade reflects following criteria for allocation of grade Reported on Official Transcript Fail A mark between 1-49 F Third Class A mark between 50-59 3 Second Class Div B A mark between 60-69 2B Second Class Div A A mark between 70-79 2A First Class A mark between 80-100 1 Result Pending An interim result RP Continuing Continuing CN 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 .
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Student Feedback
The 最新糖心Vlog 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.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the 最新糖心Vlog to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
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- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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