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The current and official versions of the course specifications are available on the web at http://www.usq.edu.au/course/specification/current.
Please consult the web for updates that may occur during the year.

STA8180 Advanced Statistics A

Semester 1, 2019 Online
Short Description: Advanced Statistics A
Units : 1
Faculty or Section : Faculty of Health, Engineering and Sciences
School or Department : School of Agric, Comp and Environ Sciences
Student contribution band : Band 2
ASCED code : 010103 - Statistics
Grading basis : Graded

Staffing

Examiner: Rachel King

Other requisites

Enrolment in this course requires the approval of the Course Examiner and appropriate Program Coordinator.
Within this course students can choose one of the topics, each of which has different prerequisites (or equivalent) as outlined below, or on approval of the examiner.

Time Series Analysis: (prerequisite STA3300)

Applied Experimental Design: (prerequisite STA2300) This topic is not available to students who have already undertaken or intend to undertake STA3300

Rationale

This course provides flexibility in honours and postgraduate programs to cater for the widely varying interests and chosen specialisations of students. Statisticians need to be proficient in a wide range of statistical concepts and techniques. Many of these are either only touched on or omitted from undergraduate programs. An opportunity to broaden the students' knowledge-base with more advanced statistical techniques is provided in this course.

Synopsis

This course provides the opportunity for a student to pursue an area of study that will complement the other studies in the student's program. Typically the course will consist of specialised investigations extending knowledge and skills in a certain area. The studies could involve, for example, directed readings, a project (where appropriate), or some other approved activity which would complement the student's studies in the program.

Objectives

On completion of this course students will be able to

  1. demonstrate advanced knowledge and skills in the study area chosen.

Topics

Description Weighting(%)
1. The study area chosen will be approved after the student consults with the Course Examiner and the appropriate Program Coordinator. Students should nominate the topic they wish to study when contacting the Course Examiner to enquire whether the topic and a suitable supervisor will be available in their semester of study, and for formal approval to enrol. One of the following topics can be chosen. The content of the course may vary from student to student. The weighting of the sub-topics within this unit depends on the topic chosen and will be discussed with the supervisor.

Time Series Analysis: This course consists of advanced studies in time series analysis. Topics will include: identification, estimation, testing and forecasting for univariate and multivariate models of time series; the spectral representation of a time series; non-linear models, including identification, estimation, testing and forecasting; cointegrated models.

Applied Experimental Design (see STA3300 for topics)
100.00

Text and materials required to be purchased or accessed

ALL textbooks and materials available to be purchased can be sourced from USQ's Online Bookshop (unless otherwise stated). (https://omnia.usq.edu.au/textbooks/?year=2019&sem=01&subject1=STA8180)

Please contact us for alternative purchase options from USQ Bookshop. (https://omnia.usq.edu.au/info/contact/)

Applied Experimental Design: see STA3300 for text.
Time Series Analysis: no text.

Reference materials

Reference materials are materials that, if accessed by students, may improve their knowledge and understanding of the material in the course and enrich their learning experience.

Student workload expectations

Activity Hours
Assessments 20.00
Private Study 97.00
Project Work 40.00
Supervisor Consultation 15.00

Assessment details

Description Marks out of Wtg (%) Due Date Notes
Assignment 1 40 40 06 Jun 2019
Assignment 2 (Project) 60 60 06 Jun 2019

Important assessment information

  1. Attendance requirements:
    There are no attendance requirements for this course. It is the students' responsibility to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration.

  2. Requirements for students to complete each assessment item satisfactorily:
    To complete an assessment item satisfactorily, students must obtain at least 50% of the marks available for that assessment item.

  3. Penalties for late submission of required work:
    Students should refer to the Assessment Procedure http://policy.usq.edu.au/documents.php?id=14749PL (point 4.2.4)

  4. Requirements for student to be awarded a passing grade in the course:
    To be assured of receiving a passing grade a student achieve at least 50% of the total weighted marks available for the course.

  5. Method used to combine assessment results to attain final grade:
    The final grades for students will be assigned on the basis of the weighted aggregate of the marks obtained for each of the summative assessment items in the course.

  6. Examination information:
    There is no examination in this course.

  7. Examination period when Deferred/Supplementary examinations will be held:
    There will be no Deferred or Supplementary examinations in this course.

  8. University Student Policies:
    Students should read the USQ policies: Definitions, Assessment and Student Academic Misconduct to avoid actions which might contravene University policies and practices. These policies can be found at http://policy.usq.edu.au.

Other requirements

  1. Computer, e-mail and Internet access:
    Students are required to have access to a personal computer, e-mail capabilities and Internet access to UConnect. Current details of computer requirements can be found at http://www.usq.edu.au/current-students/support/computing/hardware.

  2. Students can expect that questions in assessment items in this course may draw upon knowledge and skills that they can reasonably be expected to have acquired before enrolling in this course. This includes knowledge contained in pre-requisite courses and appropriate communication, information literacy, analytical, critical thinking, problem solving or numeracy skills. Students who do not possess such knowledge and skills should not expect the same grades as those students who do possess them.