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STA8180 Advanced Statistics A

Semester 1, 2016 External
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

Contents on this page


Examiner: Rachel King

Other requisites

Enrolment in this course requires the approval of the 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: STA3300
Applied Experimental Design: STA2300 (this topic is not available to students who have already undertaken or intend to undertake STA3300)
Advanced Statistical Inference: STA2302
Data Analysis and Research Reporting no prerequisite (this topic is not available to students who have already undertaken or intend to undertake STA2300, STA3100 or the Statistical Literacy in Middle Schooling topic in STA8190)

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 //


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.


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.


On completion of this course students will be able to

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


Description Weighting(%)
1. The study area chosen will be approved after the student consults with the supervisor, examiner and the appropriate Program Coordinator. Students may be directed to a certain complementary study, or they may be asked to nominate an appropriate study. The examiner will have a list of potential supervisors available for each topic. It is the student's responsibility to then contact a potential supervisor.. 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.

Advanced Statistical Inference: This course extends the statistical theory and methods covered in STA2302 Statistical Inference. Topics include: Methods for finding parametric point estimators and their properties; Test of simple and composite hypotheses, the multivariate normal and t distributions, and pretest and shrinkage estimation.

Applied Experimental Design (see STA 3300 for topics)

Data Analysis and Research Reporting: Basic statistical concepts, methods and skills necessary for students in business, commerce, psychology and the physical sciences to collect, appraise, present, analyse and interpret data are developed in this course. Emphasis is placed on understanding the basic concepts and principles of dealing with data, in particular descriptive and inferential statistics. Because these concepts and methods are interdisciplinary in nature, students will encounter problems from many sources including their own area of interest. The use of statistical software is a core component of the course. Students are required to apply knowledge gained through this course to develop, conduct and report on a research project. The mathematical underpinnings of the methods used in this course are not covered. Other statistics courses deal with this aspect.

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). (

Please contact us for alternative purchase options from USQ Bookshop. (

  • Depending on the topic chose one of the following: Time Series Analysis: no text Applied Experimental Design (see STA 3300 for text) Advanced Statistical Inference; no text Data Analysis and Research Reporting (see STA2300 for 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 90.00
Project Work 40.00
Supervisor Consultation 15.00

Assessment details

Description Marks out of Wtg (%) Due Date Notes
Assignment 1 40 40 10 Jun 2016
Assignment 2 (Project) 60 60 10 Jun 2016

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 satisfactorily complete an individual assessment item a student must achieve at least 50% of the marks or a grade of at least C.

  3. Penalties for late submission of required work:
    Students should refer to the Assessment Procedure (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