Note: This is an archived Handbook entry from 2016.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2016:Semester 1, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 3 x one hour lectures per week, 1 x one hour practice class per week. |
Total Time Commitment:
Estimated total time commitment of 170 hours
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorDr Sandy Clarke
This subject teaches students to become critical users of data-based evidence. Future journalists, political scientists, sociologists, lawyers, health professionals, psychologists, environmental scientists, business people, engineers, scientists and teachers will develop skills in identifying the strengths and weaknesses of arguments and reports based on quantitative evidence, and learn to evaluate reasoning that uses probabilistic ideas.
Data-based evidence is found in the media, in academic research and in many aspects of everyday life. The subject examines ways of judging the quality of quantitative information, and the strength of conclusions drawn from it, including concerns in establishing causality. It discusses how variability may be characterised and modelled in a wide variety of settings including public opinion, health, sport, legal disputes, and the environment. It covers good and bad ways of examining evidence in data. The subject deals with judging the likelihood of events, common pitfalls in thinking about probability, measuring risk in medical contexts and quantifying uncertainty in conclusions. It describes how data-based evidence can contribute to the accumulation of knowledge.
On completion of this subject students should be able to
and should understand
|Prescribed Texts:|| |
|Breadth Options:|| |
This subject potentially can be taken as a breadth subject component for the following courses:
You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
Students with a breadth of knowledge across disciplines must be able to understand and critically evaluate the methodologies and research findings based on data. This subject aims to provide students with these critical thinking skills. It will be important for any student wishing to develop generic research and problem-solving skills. The subject will expose students to the application of data-based evidence across a range of disciplines, and contribute to their developing interdisciplinary understanding.
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