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.

Note: Graduate students attend joint classes with undergraduates but are assessed separately.

Learning Outcomes

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

1. Methodically apply different experimental approaches in biology with deep understanding on how to use experimental models.
2. Proficiently apply R programming skills and be able to identify, choose and apply proper R packages to address biological problems.
3. Design biological experiments to address critical questions in biology.
4. Demonstrate technical proficiency in the use of appropriate analysis, and interpretation of qualitative and quantitative data.
5. Apply, and critically assess the results of relevant statistical techniques in the context of the analysis of biological measurements.
6. 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 theoretical designs of several 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 research groups.

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)

Ebook versions available through the course Canvas site.

Examination Material or equipment

Laptop computer with R and RStudio and internet access.

Required Resources

A modern laptop with WiFi and ANU VPN connectivity is a must. Students are expected to bring their laptop to the course workshops. The laptop should have the current version of R and RStudio installed (https://posit.co/download/rstudio-desktop/ ). The laptop's battery should be good enough to last for at least 3 hours.

Recommended Resources

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 laptop computer. Mobile devices may work well for the lectures, but for the workshop a laptop computer is necessary.
• 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	Recap on Probability. Coding in R with RStudio.	Setup of RStudio on students' laptops. Learning basics of R. Recapitulation of probability concepts.
2	Mean, Variation, Models, Hypotheses and Errors.	10 min. quiz and post-workshop report.
3	Comparing Groups - Categorical and Continuous Data.	10 min. quiz and post-workshop report.
4	Analysis of Variance.	10 min. quiz and post-workshop report.
5	Principles of Experimental Design and Linear Regression.	10 min. quiz and post-workshop report.
6	Generalized Linear Regression.	10 min. quiz and post-workshop report. Assignment 1 Hand-Out.
7	Models, Statistics, and The Sampling Distribution.	10 min. quiz and post-workshop report.
8	Variability and Statistical Power.	10 min. quiz and post-workshop report. Assignment 1 Hand-In.
9	Design and Analysis of Experiments.	10 min. quiz and post-workshop report.
10	Maximum Likelihood and Likelihood Ratio Test.	10 min. quiz and post-workshop report. Assignment 2 Hand-Out.
11	Modelling and Simulations.	10 min. quiz and post-workshop report. Post. Grad. (PG) Quiz.
12	Modelling and Simulations.	10 min. quiz and post-workshop report. Assignment 2 Hand-In.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Assignment 1 - Statistical Data Analysis in R	15 %	24/09/2025	08/10/2025	1,2,3,4,5
Assignment 2 - Statistical Modelling and Experimental Designs	15 %	22/10/2025	*	1,2,3,4,5,6
Weekly Quiz and report during the Workshop	30 %	*	*	1,2,3,4,5
Post Grad (PG) Quiz	10 %	17/10/2025	24/10/2025	1,2,3,4,5,6
Final exam	30 %	*	*	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

Policies

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:

• Student Assessment (Coursework) Policy and Procedure
• Special Assessment Consideration Policy and General Information
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure

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

Participation in lectures - although highly recommended - is not compulsory. In-person participation in the workshops is compulsory. All lectures will be delivered on-campus, and the recordings will be available on the course Echo360 site. Workshops will be delivered on-campus, and will not be recorded.

Examination(s)

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

Assignment 1 - Statistical Data Analysis in R

A set of statistical data analysis problems. Description of performed experiments and the resulting data will be given. Students will be expected to transform, present, and critically analyze the data, and draw conclusions. The delivery is an R Markdown document with R code and open text solutions to the tasks. Value is 15% of the course grade.

Assessment Task 2

Assignment 2 - Statistical Modelling and Experimental Designs

A set of biological experimental problems will be given. Students will be expected to propose and critically discuss appropriate experimental designs, perform statistical modelling and analysis of the data. The delivery is an R Markdown document with R code and open text solutions to the tasks. Value is 15% of the course grade.

Assessment Task 3

Weekly Quiz and report during the Workshop

Each workshop starts from a 10 minutes Canvas quiz and ends with report submission. Each quiz/report combination is 3%. The ten best weeks outcomes will count towards the course grade. The combined value of the quizzes/reports is 30% of the course grade. The quiz/report in week 1 is a try-out, and it's mark will not be counted.

Assessment Task 4

Post Grad (PG) Quiz

Canvas Quiz for Post-Graduate Students. Approx. 20 question covering all material learnt in the course so far. The questions in this quiz will assess the extended knowledge expected from post graduate students.

Assessment Task 5

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).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents undergraduate and ANU College students
• PARSA supports and represents postgraduate and research students