• Class Number 8701
  • Term Code 3060
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Marcin Adamski
    • Prof Adrienne Nicotra
    • Prof Dave Rowell
    • Dr Marcin Adamski
    • Dr Teresa Neeman
  • Class Dates
  • Class Start Date 27/07/2020
  • Class End Date 30/10/2020
  • Census Date 31/08/2020
  • Last Date to Enrol 03/08/2020
SELT Survey Results

This course will explore the ways biologists generate and assess evidence applying a variety of statistical techniques. The use of biological models from bacteria, plants and animals will be discussed, with their advantages and limitations. The value of different experimental approaches including hypothesis-driven research and large scale data generation, such as genome sequencing projects will be considered.  Quantitative reasoning and analysis will be introduced with examples of its application to biological problems.  Students will participate in practical exercises to develop and test hypotheses and then, as a group, compare and contrast the application of statistical approaches to interpret the data.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

On satisfying the requirements of this course, students will have the knowledge and skills to:

  1. Apply an advanced understanding of when to apply different experimental approaches in biology and how to use experimental models.
  2. Design biological experiments to address critical questions in biology.
  3. Demonstrate technical proficiency, appropriate analysis and interpretation of qualitative and quantitative data
  4. Describe, apply, and critically assess the results of relevant statistical techniques in the context of the analysis of biological measurements
  5. Integrate and apply the knowledge gained from specific research projects to problem solving in other areas of biology.

Research-Led Teaching

Students will design and perform an in-lab experiment as well as perform theoretical designs of several other experiments and analyze provided data. They will write reports on these activities. The data will be analysed using the techniques covered in lectures. Students will use the same analytical techniques normally used in the School research laboratories.

Additional Course Costs

Textbooks use in this course. The textbooks be can purchased, but they are also available in ANU library. The list of advised textbooks will be provided on the course Wattle page.

Examination Material or equipment

Non-programmable scientific calculator.

Required Resources

Students must have laptops with internet and ANU VPN connectivity and non-programmable scientific calculators.

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Other Information

The course materials, including lecture presentation slides and workshop's and practical manuals will be made available on the course Wattle page.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction to programming in R with RStudio. Setup of RStudio on students' laptops and access to the course RStudio server. Learning R.
2 Introduction to probability and statistics. R and RStudio learning with focus on statistical problems.
3 Statistical Tests: Chi-square/Fisher Exact and t-Test. Continued learning of R in statistics with focus on statistical hypotheses and tests. Handout of Assignment 1.
4 Linear regression and ANOVA. Continued learning of R and RStudio in statistics with focus on linear regression and analysis of variance.
5 Planning of experiments and data analysis with t-Test. The yeast UV-radiation experiment: Workshop on experimental design and data analysis. Hand-in of Assignment 1, handout of Assignment 2.
6 Planning of experiments - the seed germination practical. Lecture, workshop and practical related to the seed-germination experiment.
7 Experimental data analysis with ANOVA - the seed germination practical. Two workshops related to the seed-germination experiment. Hand-in of Assignment 2, handout of the seed-germination lab report.
8 Critical analysis of experimental design and data analysis in published papers. Journal-club style lectures and a workshop focused on published experimental design approaches and the statistical data analysis.
9 Effect of structure of variance in experimental designs. Shorter week due to Labor Day, exact subject of the workshop will be decided later. Hand-in of the lab report, handout of Assignment 3.
10 Statistical approaches in massive sequencing experiments with focus on gene expression data from RNASeq. Workshop on RNASeq gene expression data analysis, intensive use of R and R packages. Handout of PG student Assignment
11 Bayesian Inference in Biological Data Analysis. Workshop on statistical simulations and Bayesian approaches in biological data analysis, intensive use of R. Hand-in of Assignment 3.
12 Final lectures and wrapping up the content of the course. Material review, discussions and exam practice during the last workshop. Hand-in of PG student Assignment

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 - Probability & Statistics 10 % 28/08/2020 11/09/2020 1,2,3,4,5,6
Assignment 2 - Yeast UV Radiation 10 % 25/09/2020 09/10/2020 1,2,3,4,5,6
Lab Report - Seed Germination Experiment 10 % 23/10/2020 05/11/2020 1,2,3,4,5,6
Assignment 3 - Journal Club 20 % 09/10/2020 23/10/2020 1,2,3,4,5
One online quiz 10 % 04/10/2020 25/10/2020 1,2,4,5
Final exam 30 % 05/11/2020 03/12/2020 1,3,4,5,6
PG Students Assignment - Essay 10 % 30/10/2020 12/11/2020 1,3,4,5,6

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Integrity . In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


Participation in lectures, tutorials, workshops and labs is not compulsory. All lectures will be delivered online and the recordings will be available on the course Echo360. Tutorials and workshops will be delivered in classroom and, at the same time online with Zoom. The Zoom sessions will be recorded and made available on the course Echo360. The lab (Friday, week 36) will be delivered only face-to-face and will not be recorded. The remote students will be provided with description of the lab activities and ready-to-use data to analyze. All students will need to submit the lab report.


Please note, that where a date range is used in the Assessment Summary in relation to exams, the due date and return date indicate the approximate timeframe in which the exam will be held and results returned to the student (official end of Semester results released on ISIS). Students should consult the course wattle site and the ANU final examination timetable to confirm the date, time and venue of the exam.

Assessment Task 1

Value: 10 %
Due Date: 28/08/2020
Return of Assessment: 11/09/2020
Learning Outcomes: 1,2,3,4,5,6

Assignment 1 - Probability & Statistics

Probability and Statistical problem sets. The delivery is an R Markdown document with R code and open text solutions to the tasks. Barring any unforeseen circumstances, we plan to return all assignments no later than two weeks after submission.

Assessment Task 2

Value: 10 %
Due Date: 25/09/2020
Return of Assessment: 09/10/2020
Learning Outcomes: 1,2,3,4,5,6

Assignment 2 - Yeast UV Radiation

Determine the effects of sunlight on yeast UV repair. The delivery is a report stating the experiment objective and design, results and the conclusion. Barring any unforeseen circumstances, we plan to return all assignments no later than two weeks after submission.

Assessment Task 3

Value: 10 %
Due Date: 23/10/2020
Return of Assessment: 05/11/2020
Learning Outcomes: 1,2,3,4,5,6

Lab Report - Seed Germination Experiment

Use of replicated blocked experimental designs in seed germination of Australian native plants. The delivery is a report stating the experiment objective and design, results and the conclusion. Barring any unforeseen circumstances, we plan to return all assignments no later than two weeks after submission.

Assessment Task 4

Value: 20 %
Due Date: 09/10/2020
Return of Assessment: 23/10/2020
Learning Outcomes: 1,2,3,4,5

Assignment 3 - Journal Club

Perform critical analysis of a selected journal paper. The delivery is a report critically discussing the paper objectives, design of the experiments, the results and the conclusion. Barring any unforeseen circumstances, we plan to return all assignments no later than two weeks after submission.

Assessment Task 5

Value: 10 %
Due Date: 04/10/2020
Return of Assessment: 25/10/2020
Learning Outcomes: 1,2,4,5

One online quiz

Probability and Statistical problem sets. The delivery is online quiz on Wattle.

Assessment Task 6

Value: 30 %
Due Date: 05/11/2020
Return of Assessment: 03/12/2020
Learning Outcomes: 1,3,4,5,6

Final exam

One final exam, 2 hours, of statistical problems.

The date range in the Assessment Summary indicates the start of the end of semester exam period and the date official end of semester results are released on ISIS. Please check the ANU final Examination Timetable http://www.anu.edu.au/students/program-administration/assessments-exams/examination-timetable to confirm the date, time and location exam.

Assessment Task 7

Value: 10 %
Due Date: 30/10/2020
Return of Assessment: 12/11/2020
Learning Outcomes: 1,3,4,5,6

PG Students Assignment - Essay

Statistical design of experiments in practice. The delivery is an essay discussing aspects of statistical experiment design in practice. Barring any unforeseen circumstances, we plan to return all assignments no later than two weeks after submission.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.

The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.

The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Returning Assignments

Marked hard-copy assignments will be returned at the Biology Teaching and Learning Centre. A Wattle announcement will be made when marked assignments are available for collection.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

No resubmission of assignments is allowed.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dr Marcin Adamski

Research Interests

Genomic and high-throughput sequencing experiments; scientific computing; experimental designs in biology.

Dr Marcin Adamski

By Appointment
By Appointment
Prof Adrienne Nicotra
6125 9763

Research Interests

Prof Adrienne Nicotra

By Appointment
Prof Dave Rowell
6125 0993

Research Interests

Prof Dave Rowell

By Appointment
Dr Marcin Adamski
6125 2761

Research Interests

Dr Marcin Adamski

By Appointment
By Appointment
Dr Teresa Neeman
612 54033

Research Interests

Dr Teresa Neeman

By Appointment

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