Biostatistics (10222.2)

Please note these are the 2026 details for this unit
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Biostatistics
Available teaching periods Delivery mode Location
View teaching periods On-campus
 Bruce, Canberra
EFTSL Credit points Faculty
0.125 3 Faculty Of Science And Technology
Discipline Study level HECS Bands
Academic Program Area - Science Level 2 - Undergraduate Intermediate Unit Band 2 2021 (Commenced After 1 Jan 2021)
Band 3 2021 (Commenced Before 1 Jan 2021)
This unit is focused on developing a comprehensive understanding of scientific methods and how to analyse scientific data. The unit will include data from current research projects being conducted within the faculty. The unit aims to cover as many different science disciplines as possible in order to present students with the breadth of statistical methods available and to learn the different analytical approaches. Data from disciplines such as Ecochemistry, Wildlife and Forensic Genetics, Health, and Conservation Ecology will be used. Students will develop their problem solving skills and are expected to apply these to the data sets introduced during the unit.

Learning outcomes

On successful completion of this unit, students will be able to:
1. Be able to apply prior knowledge of scientific methods in the analysis and interpretation of scientific data;
2. Demonstrate knowledge of existing statistical methodologies such as linear regression, ANOVA and hypothesis testing using parametric and non-parametric tests;
3. Develop an understanding of the key concepts underpinning each method and the associated assumptions and limitations. Acquiring problem solving skills to enable the resolution of new problems and data types
4. Be able to communicate effectively using well-developed scientific thinking; and
5. Develop independent critical scientific thinking.


Graduate attributes

1. UC graduates are professional - communicate effectively
1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - take pride in their professional and personal integrity
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas
3. UC graduates are lifelong learners - be self-aware
3. UC graduates are lifelong learners - evaluate and adopt new technology
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development


Prerequisites

11723 Data Analysis Skills for Science OR 1809 Data Analysis in Science

Corequisites

None.

Incompatible units

7904 Forensic Statistics

Equivalent units

6913 Biometry AND 6542 Experiment Design and Analysis

Assumed knowledge

None.
Availability for enrolment in 2026 is subject to change and may not be confirmed until closer to the teaching start date.
Year Location Teaching period Teaching start date Delivery mode Unit convener
2025 Bruce, Canberra Semester 1 03 February 2025 On-campus Dr Bernd Gruber
2026 Bruce, Canberra Semester 1 16 February 2026 On-campus Dr Bernd Gruber
The information provided should be used as a guide only. Timetables may not be finalised until week 2 of the teaching period and are subject to change. Search for the unit timetable.

Required texts

Textbook (recommended, but not required, some copies are available at the library)

As the unit consists of a variety of statistical methods there is no single book covering all the material taught in the unit. Additional material will be supplied via Canvas for more specialised methods. A deep understanding of linear models and all of its variants are the most important part of the unit therefore the following books are highly recommended:

Andy Field et al., Discovering Statistics Using R 1st Edition, Sage, ISBN-13: 978-1446200469

         or

Crawley, Michael J , Statistics: An Introduction Using R 2nd Edition, Wiley, ISBN-13: 978-1118941096

Leps, Jan & Petr Smilauer, Biostatistics with R - An Introductory Guide for Field Biologists, ISBN: 9781108727341

Additional recommended books are:

            Alan Zuur, Mixed Effect Models and Extensions in Ecology with R, Springer, ISBN 978-0-387-87458-6

            Borcard et al., Numerical Ecology using R, Springer, ISBN 978-1-4419-7976-6

            John K. Kruschke , Doing Bayesian Analysis using R, Elsevier, ISBN: 9780124058880

Other Recommended Reading:

    There are multiple excellent resources freely available, which will be provided via links on the unit's Canvas site.

Submission of assessment items

Special assessment requirements

Assessable exercises are completed in and out of class and are to be submitted electronically. Detailed description of each assessable exercise and instructions are provided via Canvas. Details of expectations, submission requirements, assessment criteria and other information are given in the work descriptions in addition to the desired generic skills and graduate attributes to be achieved. All generic skills and graduate attributes are relevant in these assessable exercises.

Students should keep a back-up copy of any assessment item that has been submitted.

The unit convenor reserves the right to question students on any of their submitted work for moderation and academic integrity purposes.

Attendance at the practical lab classes is highly recommended. Without consistent attendance at the practical lab classes this unit is very difficult to complete successfully.

Students must apply academic integrity in their learning and research activities at UC. This includes submitting authentic and original work for assessments and properly acknowledging any sources used.

Academic integrity involves the ethical, honest and responsible use, creation and sharing of information. It is critical to the quality of higher education. Our academic integrity values are honesty, trust, fairness, respect, responsibility and courage.

UC students have to complete the Academic Integrity Module annually to learn about academic integrity and to understand the consequences of academic integrity breaches (or academic misconduct).

UC uses various strategies and systems, including detection software, to identify potential breaches of academic integrity. Suspected breaches may be investigated, and action can be taken when misconduct is found to have occurred.

Information is provided in the Academic Integrity Policy, Academic Integrity Procedure, and University of Canberra (Student Conduct) Rules 2023. For further advice, visit Study Skills.

Learner engagement

Lectures are recorded and available via the canvas site. To successfully complete the unit it is expected to spend around 150 hours of work on the unit, which equates around 6-7 hours per week in addition to lectures, labs and assignments. An indicative workload breakdown can be found below:

  lectures labs assignments additional study total
hours 24 24 20 82   150

Teaching philosophy and conduct

The teaching philosophy of the unit convener and associated staff is that all work in this 2nd year unit is not just a one-way stream of information from the staff to the students, but a collaborative discovery journey of both students and staff. To promote deep understanding the unit is designed to guide and challenge the students to reinvent "the wheel(s)" for themselves rather than provide straight recipes. It is therefore necessary and expected that the students fully commit themselves to the unit, by coming prepared to lectures, participate actively in group activities, lectures, tutorials and labs and spend abundant time on self-study. The students may expect that the staff will create a supportive intellectual environment and teach and mentor to the best of their abilities in a professional respectful manner. The staff and unit convener expect in exchange that the students will behave in an equally professional and respectful manner. The staff may, from time to time, make general (or discrete individual) suggestions towards improving professional behaviour, with the aim to improve the learning experience in the unit or to guide students in their efforts to increase their chances of future professional employment. 

Participation requirements

Attendance at labs is highly recommended. Students will have difficulty completing computer practical exercises without the knowledge imparted during lectures. Therefore it is important that students come prepared to lectures by reading the suggested material and revising the content of the previous weeks.

Participation in tutorials/labs is highly recommended for the successful participation of this unit, and attendance will be recorded. Contact the Unit Convener as soon as possible to negotiate an alternate lab class later in the week (if available). 

In all cases of absence, sickness or personal problems it is the student's responsibility to ensure that the unit Convener is informed.

Required IT skills

Students are expected to have a basic level of IT understanding and computer literacy. Moreover the ability to work within Rstudio is a requirement. In case students are not feeling comfortable with this requirement, please contact the unit convenor before beginning of the course to explore avenues to meet this requirement at the start of the unit. Specialist IT skills are expected to be acquired over the semester in practical lab classes.

            The discussion forum at the unit's Canvas site is for asynchronous communication with other students and staff.  It is asynchronous because the parties communicating with each other do not all have to be sitting at the computer at the same time. 

            You do not have to install any special software to access the discussion forum - just use your browser.

            To use the Discussion Forum, you need to be able to:

  • Navigate through the various topics and conversations
  • Add your own topics and converse on topics (threads)

             Please note that the Discussion Forum is visible to all academic staff and all students enrolled in the unit.  If you have a private enquiry, use email or the personal messaging facility.

In-unit costs

There are some costs associated with this Unit such as the purchase of recommended books. Software is provided with no cost associated with it. Students are able to install R and Rstudio on their own computers, but should be aware that if they decide to do their assessments on a University computer, they need to be familiar with the Windows operating system.

Work placement, internships or practicums

None

Additional information

Students should keep a back-up copy of any assessment item that has been submitted.

Use of UC student email
Students are also expected to use their university-provided email accounts to facilitate communication with the Lecturer. If alternative private email accounts are used by students, it is the student's responsibility to set up and re-direct email messages from this university provided email account to their private email accounts. It is expected that email messages will be the main mode of contact outside scheduled classes.

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