- Code BIOL2202
- Unit Value 6 units
Science is fundamentally about testing ideas, not collecting facts. But how do we test ideas? We do so by analysing numbers to reveal patterns, and then by designing experiments to exclude competing ideas that might explain what causes these patterns. In this course, you will discover how to design experiments and analyse data. You’ll then be equipped to critically assess scientific claims that you hear in the media. Think about how much of the news is about alleged medical breakthroughs, causes of health problems, and claims that one economic policy is better than another. We want to help you to sift out fake news, identify misleading ways to describe data and allow you to assess the importance of different factors in explaining the patterns we see in the world. This is a core life skill. And, naturally, if you take this course you’ll be better equipped to take the path to becoming a biologist yourself.
This course will explore the ways biologists design experiments, generate data and assess evidence using a variety of statistical techniques. We will discuss the value of different scientific approaches, including hypothesis-driven experiments and exploration of large-scale data generation–such as genome and transcriptome sequencing projects. We’ll consider examples from microbial, animal and plant biology, and you will carry out exercises to develop and test hypotheses, and critically interpret the results. You will have the opportunity to participate in all stages of a biological experiment. This will include the conception and design of a study, laboratory work, analysis of the data, drawing conclusions, writing the report and engaging graphical ways to present your findings. The R programming language will be taught and used throughout the course. Students will be required to use their laptop computers.
Honours Pathway Option (HPO): This course offers optional HPO and ASE add-ons for undergraduate students.
HPO and ASE students will be required to demonstrate greater depth of understanding of the content of the course. They will undertake an independent or group inquiry-based research project. Students will be required to write and present report from the project. The project will include:
- literature review,
- analysis and critical evaluation of research data, and
- presentations of the research.
The fields of research will include:
- genetics and genomics,
Either add-on will count for 20% of the mark for enrolled students. In this case the regular course assessments (Assignments x3, Lab report, Mid-term quiz and Final Exam) will be scaled down to 80%.
Students participation in these options must be approved by the course convener. Students should contact the course convener regarding availability and specific requirements before or immediately after the course start.
Upon successful completion, students will have the knowledge and skills to:
- Understand when to apply different experimental approaches in biology and how to use experimental models.
- Proficiently apply R programming skills in RStudio environment for experimental data analysis and visualization.
- Create simple biological experiment designs to address specific questions.
- Demonstrate practical skills in analysis and interpretation of qualitative and quantitative data.
- Describe, apply, and evaluate the results of relevant statistical techniques in the context of the analysis of biological measurements.
- Apply the knowledge gained from specific research projects to problem solving in other areas of biology.
- For HPO/ASE only: Proficiency in finding and use of literature to help with research project design. Design and conduct of a research, inquiry-based project. Proficiency in biological data analysis with use of various computational techniques. Demonstrated ability to present findings from the research project in form of a short seminar. Ability to answer questions and participate in discussion related to the seminar to argue and defend your findings and conclusions.
Previous experience in STAT1003 or another similar course would be helpful.
- Lab report (20) [LO 1,2,3,4,5]
- 3 x Assignments (30) [LO 1,2,3,4,5,6]
- Mid-term quiz (10) [LO 1,2,4,5]
- Final Exam (40) [LO 1,3,4,5,6]
- For HPO/ASE: All assessments above will be at 80% each for Lab report; assignments; mid term quiz and final exam. Additional assessment will be Project report including 15 min presentation. (20) [LO 7]
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The expected workload will consist of approximately 130 hours throughout the semester including:
- Face-to face component which may consist of approx. 2 x 1-hour lectures per week plus 12 x 3-hour workshops/tutorials/practicals throughout the semester. Together there will be approx. 60 hours of in-class component per semester.
- Approximately 70 hours of self directed study which will include preparation for lectures and workshops/tutorials and labs and other assessment tasks including written assignments, quizzes, and an exam.
Students are expected to actively participate and contribute towards discussions.
To be determined
Requisite and Incompatibility
Reading materials will be provided throughout the course. The primary textbook will be Whitlock and Schluter, The Analysis of Biological Data, edition 2 or 3.
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
Offerings, Dates and Class Summary Links
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|6321||26 Jul 2021||02 Aug 2021||31 Aug 2021||29 Oct 2021||In Person||N/A|