- Class Number 6350
- Term Code 3160
- 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 26/07/2021
- Class End Date 29/10/2021
- Census Date 14/09/2021
- Last Date to Enrol 02/08/2021
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.
Upon successful completion, students will have the knowledge and skills to:
- Methodically apply different experimental approaches in biology with deep understanding on how to use experimental models.
- Proficiently apply R programming skills and be able to identify, choose and apply proper R packages to address biological problems.
- Design biological experiments to address critical questions in biology.
- Demonstrate technical proficiency in the use of appropriate analysis, and interpretation of qualitative and quantitative data.
- Apply, and critically assess the results of relevant statistical techniques in the context of the analysis of biological measurements.
- Integrate and apply the knowledge gained from specific research projects to problem solving in other areas of biology.
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.
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.
- 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
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
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.
The course materials, including lecture presentation slides and workshop's and practical manuals will be made available on the course Wattle page.
|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 task||Value||Due Date||Return of assessment||Learning Outcomes|
|Assignment 1 - Probability & Statistics||10 %||18/08/2021||25/08/2021||1,2,3,4,5,6|
|Assignment 2 - Yeast UV Radiation||10 %||01/09/2021||22/09/2021||1,2,3,4,5,6|
|Lab Report - Seed Germination Experiment||10 %||29/10/2021||12/11/2021||1,2,3,4,5,6|
|Assignment 3 - Journal Club||20 %||06/10/2021||20/10/2021||1,2,3,4,5|
|One online quiz||10 %||03/09/2021||20/09/2021||1,2,4,5|
|Final exam||30 %||04/11/2021||02/12/2021||1,3,4,5,6|
|PG Students Assignment - Essay||10 %||22/10/2021||12/11/2021||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:
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 is not compulsory. Participation in tutorials, workshops and labs - in-class or remote - is compulsory. All lectures will be delivered online and the recordings will be available on the course Echo360 site. Tutorials and workshops will be delivered in classroom and, at the same time online with Zoom. The Zoom sessions will be recorded and will be available on request on the course Echo360 site. The lab (Friday, week 40) 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
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
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
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
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
Learning Outcomes: 1,2,4,5
One online quiz
Probability and Statistical problem sets. The delivery is online quiz on Wattle.
Assessment Task 6
Learning Outcomes: 1,3,4,5,6
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
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 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.
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.
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 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.
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.
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.
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
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- 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.
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Genomic and high-throughput sequencing experiments; scientific computing; experimental designs in biology.
Dr Marcin Adamski
Prof Adrienne Nicotra
Dr Marcin Adamski