• Class Number 6014
  • Term Code 3360
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Marcin Adamski
    • Prof Adrienne Nicotra
    • Dr Marcin Adamski
    • Dr Teresa Neeman
  • Class Dates
  • Class Start Date 24/07/2023
  • Class End Date 27/10/2023
  • Census Date 31/08/2023
  • Last Date to Enrol 31/07/2023
SELT Survey Results

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,
  • epigenetics,
  • biostatistics.

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.

Learning Outcomes

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

  1. Understand when to apply different experimental approaches in biology and how to use experimental models.
  2. Proficiently apply R programming skills in RStudio environment for experimental data analysis and visualization.
  3. Create simple biological experiment designs to address specific questions.
  4. Demonstrate practical skills in analysis and interpretation of qualitative and quantitative data.
  5. Describe, apply, and evaluate the results of relevant statistical techniques in the context of the analysis of biological measurements.
  6. Apply the knowledge gained from specific research projects to problem solving in other areas of biology.
  7. 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.

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 used in this course:

  • Introductory R by R.J. Knell (e-book)
  • The Analysis of Biological Data by M.C. Whitlock and D. Schluter (book, or e-book)

The textbooks be can purchased, but they are also available in ANU library.

Examination Material or equipment

Laptop computer with R and RStudio and internet access.

Required Resources

Modern laptop with internet and ANU VPN connectivity and RStudio installed. The laptop's battery should be good enough for at least 3 hours of work.

Recommended student system requirements 

ANU courses commonly use a number of online resources and activities including:

  • video material, similar to YouTube, for lectures and other instruction
  • two-way video conferencing for interactive learning
  • email and other messaging tools for communication
  • interactive web apps for formative and collaborative activities
  • print and photo/scan for handwritten work
  • home-based assessment.

To fully participate in ANU learning, students need:

  • A computer or laptop. Mobile devices may work well but in some situations a computer/laptop may be more appropriate.
  • Webcam
  • Speakers and a microphone (e.g. headset)
  • Reliable, stable internet connection. Broadband recommended. If using a mobile network or wi-fi then check performance is adequate.
  • Suitable location with minimal interruptions and adequate privacy for classes and assessments.
  • Printing, and photo/scanning equipment

For more information please see https://www.anu.edu.au/students/systems/recommended-student-system-requirements

Staff Feedback

Students will be given feedback in the following forms in this course:
  • Written comments
  • Verbal comments
  • Feedback to the whole class, to groups, to individuals, focus groups

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 site.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction to programming in R using RStudio. Setup of RStudio on students' laptops. Learning basics of R.
2 Introduction to probability and statistics. Statistical data presentation and analysis in R.
3 Statistical Tests: Chi-square/Fisher Exact and t-Test. Use of R in statistical data analysis with focus on statistical hypotheses testing. Hand-out of assignment 1.
4 Advanced experimental designs, ANOVA Continued learning of R with focus on linear regression and analysis of variance. Hand-in of assignment 1.
5 Experiments - from planning to conclusions on the example of photoreactivation in yeasts. The yeast UV-photoreactivation experiment: Design of the experiment, and analysis of the data. Hand-out of assignment 2.
6 Linear regression and non-parametric tests. Learning about more sophistacted experimental designs and analysis of multi-factor data. Hand-in of assignment 2, mid-semester quiz (Wattle).
7 Design and data analysis of experiments in Humans Journal-club style lectures and a workshop focused on experimental design approaches with focus on statistical power and size of the sample. Hand-out of assignment 3.
8 Experimental data analysis with ANOVA - the Seed of Design module - part 1. Designing of the seed germination experiment, the related in-lab practical. Hand-in of assignment 3, hand-out of the lab report.
9 Bayesian Inference in Biological Data Analysis - part 1. Bayesian approaches in biological data analysis - introduction. Recording of the germination data in the 'Seed of Design' experiment.
10 Bayesian Inference in Biological Data Analysis - part 2. Bayesian approaches in biological data analysis - introduction. Recording of the germination data in the 'Seed of Design' experiment.
11 Experimental data analysis with ANOVA - the Seed of Design module - part 2. Data analysis, discussion and conclusions from the 'Seed of Design' experiment.
12 Statistical approaches in massive sequencing experiments with focus on gene expression data from RNA-Seq. Analysis of gene expression data from RNA-Seq experiment. Intensive use of R and R packages. Recording of the germination data in the 'Seed of Design' experiment. Hand-in of the lab report.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Assignment 1 - Probability & Statistics 10 % 17/08/2023 28/08/2023 1, 2, 4, 5
Assignment 2 - Photoreactivation Experiment 10 % 31/08/2023 25/09/2023 1, 2, 3, 4, 5
Mid-semester Quiz 10 % 01/09/2023 01/09/2023 1, 2, 3, 4, 5
Assignment 3 - Data analysis in medical experiments 10 % 28/09/2023 03/10/2023 1, 2, 3, 4, 5, 6
Lab Report - Seed Germination Experiment 20 % 26/10/2023 07/11/2023 1, 2, 3, 4, 5, 6
Final exam 40 % * * 1, 2, 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 ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

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 - although highly recommended - is not compulsory. Participation in the workshops and labs - in-class or remote - is compulsory. All lectures will be delivered on-campus, and the recordings will be available on the course Echo360 site. Workshops will be delivered in on-campus, and - at the same time - online on Zoom. The lab (Friday, semester week 8) will be delivered only on-campus, 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: 17/08/2023
Return of Assessment: 28/08/2023
Learning Outcomes: 1, 2, 4, 5

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.

Assessment Task 2

Value: 10 %
Due Date: 31/08/2023
Return of Assessment: 25/09/2023
Learning Outcomes: 1, 2, 3, 4, 5

Assignment 2 - Photoreactivation Experiment

Determine the effects of photoreactivation on yeast UV-caused DNA damage. The delivery is a report stating the experiment objective and design, statistical data analysis and results, and the discussion and conclusions.

Assessment Task 3

Value: 10 %
Due Date: 01/09/2023
Return of Assessment: 01/09/2023
Learning Outcomes: 1, 2, 3, 4, 5

Mid-semester Quiz

In-classroom Wattle quiz with approximately 12 questions of equal value. The quiz questions will be related to the statistical and data analysis subjects and problems discussed in weeks 1 - 6.

Assessment Task 4

Value: 10 %
Due Date: 28/09/2023
Return of Assessment: 03/10/2023
Learning Outcomes: 1, 2, 3, 4, 5, 6

Assignment 3 - Data analysis in medical experiments

Perform critical analysis of given data from medical experiment. The delivery is an R Markdown document with R code and open text solutions to the tasks.

Assessment Task 5

Value: 20 %
Due Date: 26/10/2023
Return of Assessment: 07/11/2023
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 scientific report stating the introduction, the materials and methods, the results, and the discussion sections. The report should include the experiment objectives and design, present and discuss the results and the conclusions. It should include all the relevant references.

Assessment Task 6

Value: 40 %
Learning Outcomes: 1, 2, 3, 4, 5, 6

Final exam

Final exam, 2 hours. The exam consists of two parts:

  1. Section A - Quiz - 12 questions of equal value - 45% of the exam mark
  2. Section B - R Assignment - 3 problems of equal value - 55% of the exam mark

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.

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community 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 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 University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

The ANU uses 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. 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) a submission must be through Turnitin

Hardcopy Submission

There are no hand-written assignments requiring hardcopy submission in this course.

Late Submission

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

All assignments will be marked and feedback will be provided on the course Wattle site in the relevant assignment or TurnitIn activities. A Wattle announcement will be made when marked assignments are available.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure The Course Convener may grant extensions 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
6125 2761

Research Interests

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

Dr Marcin Adamski

Monday 12:10 13:10
Tuesday 11:10 12:10
Sunday 12:10 13:10
Prof Adrienne Nicotra
6125 9763

Research Interests

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

Prof Adrienne Nicotra

By Appointment
Dr Marcin Adamski
6125 2761

Research Interests

Dr Marcin Adamski

Monday 12:10 13:10
Tuesday 11:10 12:10
Sunday 12:10 13:10
Dr Teresa Neeman
612 54033

Research Interests

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

Dr Teresa Neeman

By Appointment

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions