MAST20031 Analysis of Biological Data
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2017:
Semester 1, Parkville - Taught on campus.Show/hide details
Timetable can be viewed here.
For information about these dates, click here.
|Time Commitment:||Contact Hours: 2 x one hour online lectures per week, 2 x one hour interactive lectures per week, 1 x one hour computer laboratory class per week. |
Total Time Commitment:
12.5 credit points from any of the following:
Study Period Commencement:
|Recommended Background Knowledge:|| |
25 points of first year Biology subjects
|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 Ben Phillips, Dr Davide Ferrari
|Subject Overview:|| |
A capacity to interpret data is fundamental to making informed decisions in everyday life. The design of experiments, analysis, and interpretation of biological data also lie at the very heart of the scientific enterprise. You cannot be a scientist without an understanding of data and design. This subject introduces you to fundamental concepts in data science for biology, with emphasis on modern statistical methods. Drawing on real biological problems and datasets, as well as drawing on data collected by the class, the lectures cover foundational concepts in experimental design and statistical modelling. The subject emphasises hands-on problem solving. As well as a solid grounding in statistical methodology, you will also develop practical skills, developing your capacity to design experiments, collect data, and analyse those data using the R statistical environment.
|Learning Outcomes:|| |
Students completing this subject should be able to:
|Prescribed Texts:|| |
Whitlock and Schluter, The Analysis of Biological Data.
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
|Generic Skills:|| |
The subject builds upon generic skills developed in first year level subjects, including the ability to critically assess and assimilate new knowledge. Students will also learn how to:
|Master of Engineering (Environmental) |
Science-credited subjects - new generation B-SCI and B-ENG.
Selective subjects for B-BMED