Basic Evidence-Based Decision Making

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Contact information

For further information or to request a quotation, please contact the Professional Education Courses Unit on:

Enquiries Phone: 02 5114 5573

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In-house delivery

UNSW Canberra Professional Education Courses may be available for in-house delivery at your organisation's premises. In-house courses allow maximum attendance without the additional travel costs. Courses can be developed to suit the specific staff development and training needs of your organisation. Recommended for groups of 10 or more.

This course will be run as a live simulcast online course presented through Microsoft Teams.  You will be required to use Excel 2016 or later during this course.

Government organisations, including defence, and industry are more and more insisting on making decisions and policies based on evidence. To make sound professional managerial decisions, it is important to take cognisance of both research and experiential evidence. In this short course, different methodologies to gather and generate evidence, analyse them, and their appropriate use in practical decision making will be covered with examples.

Prior Knowledge: No prior knowledge is assumed.


Prof. Charles S Newton obtained his PhD in Nuclear Physics from the ANU in 1975. He is an Emeritus Professor in the School of Engineering and IT, UNSW Canberra. He was the Head of the former School of Computer Science (currently a part of School of Engineering and IT) from 1993 to 2003. He was the President of National Committee of the Australian Society for Operations Research (ASOR) in 1995-96. He is the co-author of the book Optimization Modelling: A Practical Approach, Taylor & Francis /CRC Press, Boca Raton. Prof. Newton is well-known, both nationally and internationally, for his practice in Operations Research specifically for defence related problems.

Prof. Ruhul A Sarker obtained his Ph.D. in Operations Research from Dalhousie University (former TUNS), Halifax, Canada in 1992. He is currently a Professor in the School of Engineering and IT, co-ordinator of the Master of Decision Analytics program in the school, and the Director of Faculty Postgraduate Research at UNSW Canberra (located at ADFA), Australia. He was the Deputy Head of School (Research) from 2011 to 2014. Prof. Sarker’s broad teaching and research interests include decision analytics, computational intelligence, operations research, and applied optimization. He is the lead author of the book Optimization Modelling: A Practical Approach, Taylor & Francis /CRC Press, Boca Raton. Prof. Sarker has successfully obtained more than $1.5million external research grants. He was a member of the national executive committee of the Australian Society for Operations Research (ASOR) and Editor-in-chief of ASOR Bulletin from 2000 to 2011. As recognition of Prof. Sarker’s contributions to ASOR and Operations Research, ASOR awarded him an ASOR Medal (2011) and Special Service Certificate (2009). Currently, he is an associate editor of three international journals.

Course Information

This three-day course addresses evidence-based decision making. This course will address the hierarchy of evidence, the strength of the evidence, the reliability and validity of evidence. The course will also discuss the methodologies used to gather evidence, discussing the quality framework for good decision making, explaining different topics on judgement-based, behavioural, and naturalistic decision making, and discussing the biases that can occur in human-decision making and the qualitative tools applicable to the evidence-based decision-making process.

Courses will be held subject to sufficient registrations. UNSW Canberra reserves the right to cancel a course up to five working days prior to commencement of the course. If a course is cancelled, you will have the opportunity to transfer your registration or be issued a full refund. If registrant cancels within 10 days of course commencement, a 50% registration fee will apply. UNSW Canberra is a registered ACT provider under ESOS Act 2000-CRICOS provider Code 00098G.