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Major: Statistics

Major Details



Department of Statistics
Faculty of Science and Engineering

This major must be completed as part of an award. The general requirements for the award must be satisfied in order to graduate.

Requirements for the Major:

Completion of a minimum of 24 credit points including the following prescribed units:

Credit points

100 level

3cp from
Business Statistics (3)
Introductory Statistics (3)
Statistical Data Analysis (3)

200 level

Applied Statistics (3)
Statistics I (3)
Probability (3)
Introduction to Probability (3)
Computer Simulation (3)
Operations Research I (3)

300 level

Consulting in Statistical Sciences (3)
Linear Models (3)
6cp from
Graphics, Multivariate Methods and Data Mining (3)
Statistical Inference (3)
Market Research and Forecasting (3)
Design of Surveys and Experiments (3)
Statistical Computing (3)
Biostatistics and Epidemiology (3)


Units marked with a C are Capstone units.
Units marked with a P are PACE units.
Additional Information
Overview and Aims of the Program Statistics as a discipline is the development and application of methods for collecting, analysing and interpreting data. It is the science of learning from data, or converting data into knowledge.

Statistics is an essential tool for making informed decisions in all areas of business and government. Aims include:
• producing the “best” information from available data by reducing uncertainty in decision-making, and detecting patterns in the data
• designing experiment and other data collection methods to help decision-making, by estimating the present and/or predicting the future.

This major has a strong focus on the application of contemporary statistical methods and the use the latest computational techniques. The development of relevant computing skills also forms an integral part of this major.
Graduate Capabilities

The Graduate Capabilities Framework articulates the fundamentals that underpin all of Macquarie’s academic programs. It expresses these as follows:

Cognitive capabilities
(K) discipline specific knowledge and skills
(T) critical, analytical and integrative thinking
(P) problem solving and research capability
(I) creative and innovative

Interpersonal or social capabilities
(C) effective communication
(E) engaged and ethical local and global citizens
(A) socially and environmentally active and responsible

Personal capabilities
(J) capable of professional and personal judgement and initiative
(L) commitment to continuous learning

Program Learning Outcomes By the end of this program it is anticipated you should be able to:

1. demonstrate well-developed fundamental knowledge in statistics (K)
2. apply statistical principles, concepts, techniques and technology to solve routine practical and theoretical problems and interpret the results (K, T, P)
3. identify situations in which familiar techniques do not apply and learn from a range of relevant sources for appropriate alternative techniques and solve problems (K, T, P, L)
4. demonstrate an understanding in the multi-disciplinary role of statistics and the way it contributes the development in other fields of study (I, E, J, L).

5. ask appropriate questions to identify a problem and formulate it in statistical terms (T, P, I, C, J)
6. communicate information, reasoning and conclusion(s) at an appropriate statistical level to a wide range of audience both verbally and in writing (K, T, P, C, E, J)
7. critically reflect on the strength and weaknesses of yourself and your team members and suggest ways in which you and others could improve the work in the future (K, T, P, C, J, L)
8. work co-operatively as a team member (C, E, A, J)
9. make ethical decisions while collecting and analysing data and reporting findings and discuss the ethical aspects and implications of professional statistical work (K, C, E, A, J).
Learning and Teaching Methods In statistics we mainly use lectures and tutorials (or practicals) as the main learning and teaching activities. Students are expected to spend extra time in self study to improve their understanding of the content of their units.

• Lectures: where usually the theory is introduced and if possible collaborative discussion and active learning exercises are used to improve student engagement with the content of the lectures.
• Tutorials: where usually theories are put into application either within computer laboratories or small tutorial groups. Students are encouraged to work together to enable peer learning.
• Practicals: similar to the tutorials where theories are put into application by the help of tutors/demonstrators. Students are encouraged to work together to enable peer learning.
• Self study: with extra learning materials, students are expected to enhance their learning in many of the statistics major units.
Assessment Various assessment methods are used in the required units for the Statistics major which includes problem solving, producing short or full statistical reports, oral presentations, active participation in lectures and/or tutorials, online quizzes, application on statistical methods using computers (which could be assessed within a computing lab under exam conditions or as a part of assignments).
The submissions of assessments could be individual or group work. Where group work is used, a self reflection and peer assessment/feedback in the form of contribution to the assessment task is incorporated into the requirements of the assessment so that individual contributions of each student can be identified.

As well as summative assessments, we use formative assessments to help students to learn without the fear of losing marks. These formative assessments are usually in the form of submitting tutorial/practical exercises weekly.
Recognition of Prior Learning

Macquarie University may recognise prior formal, informal and non-formal learning for the purpose of granting credit towards, or admission into, a program. The recognition of these forms of learning is enabled by the University’s Recognition of Prior Learning (RPL) Policy (see and its associated Procedures and Guidelines. The RPL pages contain information on how to apply, links to registers, and the approval processes for recognising prior learning for entry or credit. 

Domestic Students
For undergraduate RPL information visit
For domestic postgraduate RPL information visit

International Students
For RPL information visit

The Department of Statistics usually will recognise only formal prior learning when granting credit toward the Major in Statistics, but may consider informal prior learning in exceptional cases.
Support for Learning

Macquarie University aspires to be an inclusive and supportive community of learners where all students are given the opportunity to meet their academic and personal goals. The University offers a comprehensive range of free and accessible student support services which include academic advice, counselling and psychological services, advocacy services and welfare advice, careers and employment, disability services and academic skills workshops amongst others. There is also a bulk billing medical service located on campus.

Further information can be found at

Campus Wellbeing contact details:
Phone: +61 2 9850 7497

Program Standards and Quality

The program is subject to an ongoing comprehensive process of quality review in accordance with a pre-determined schedule that complies with the Higher Education Standards Framework. The review is overseen by Macquarie University's peak academic governance body, the Academic Senate and takes into account feedback received from students, staff and external stakeholders.

Graduate Destinations and Employability Statistics applies to many disciplines, from the physical and social sciences to the humanities. Statisticians may work by themselves, but they usually work in a team. The team members could include research specialists, clerical personnel or computing experts who might have collected or overseen data collection.

The career opportunities for graduates of this major include statisticians, statistical programmers, research assistants and statistical analysts in research organisations, insurance companies, financial institutions, medical institutions, government departments and industries.

After a first degree there are opportunities to acquire more specialised expertise in a range of areas where applied statisticians are currently in demand at the postgraduate level. The department also offers excellent opportunities for research degrees in many specialised areas.
Assessment Regulations

This program is subject to Macquarie University regulations, including but not limited to those specified in the Assessment Policy, Academic Honesty Policy, the Final Examination Policy and relevant University Rules. For all approved University policies, procedures, guidelines and schedules visit

2017 Unit Information

When offered:
S1 Day
Permission of Executive Dean of Faculty
HSC Chinese, CHN113, CHN148