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BIOL40390

Academic Year 2026/2027

Quantitative Tools for the Life Sciences (BIOL40390)

Subject:
Biology
College:
Science
School:
Biology & Environment Science
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Assoc Professor Jonathan Yearsley
Trimester:
Summer
Mode of Delivery:
Blended
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

This module aims to equip you with the skills to professionally interpret and communicate technical information in the biological and biomedical sciences.

Topics covered include data management, data visualisation, statistical modelling, design and analysis of biological experiments, introduction to linear models and hypothesis testing using the R statistical software package.

Students will require their own laptops for this module.

About this Module

Learning Outcomes:

Students will:
1. Design a biological experiment, taking due account of independence, allocation of replicates and controls;
2. Organise and manipulate data on a computer;
3. Fit and validate a statistical model to biological data;
4. Test a null-hypothesis using a fitted statistical model;
5. Answer research questions and draw strong defensible conclusions using statistical data analysis;

Skills:
The module will contribute towards the development of the following skills:
• Effective presentation and writing of technical information
• Transparency and collaboration on data analysis projects
• R statistical language and general computer skills

Indicative Module Content:

1.Getting started with R
2.Organising and importing data
3.Exploratory data analysis
4.Distributions
5.Scientific method and hypotheses
6.Experimental design
7.Bootstrapping
8.Statistical modelling (general linear models)
8a.Model validation
8b.Regression models
8c.Models to compare groups
9.Hypothesis testing
9a.Methodology
9b.Multiple comparisons
10.Count data

UNESCO highlights a set of key competencies that support individuals in their development and support society in achieving the UN Sustainable Development Goals (SDGs). UCD has adapted these competencies and is combining them with others to form a general framework of learning competencies. This module will help you develop the competencies below to the levels specified. 
Learning Competency Additional Information Level

Collaboration

The ability to learn from others; to understand and respect the needs, perspectives and actions of others (empathy); to understand, relate to and be sensitive to others (empathic leadership); to deal with conflicts in a group; and to facilitate collaborative and participatory problem solving. Novice

Critical Thinking

The ability to question norms, practices and opinions; to reflect on one’s own values, perceptions and actions. Advanced Beginner

Systems Thinking

The ability to recognize and understand relationships; to analyse complex systems; to think of how systems are embedded within different domains and different scales; and to deal with uncertainty. Novice

Strategic

The ability to collectively develop and implement innovative actions that further sustainability at the local level and further afield. Novice

Integrated Problem Solving

The overarching ability to apply different problem-solving frameworks to complex sustainability problems and develop viable, inclusive and equitable solution options that promote sustainable development, integrating the competencies in this list. Advanced Beginner

Self-awareness

The ability to reflect on one’s own role in the local community and (global) society; to continually evaluate and further motivate one’s actions; and to deal with one’s feelings and desires. Novice

Normative

The ability to understand and reflect on the norms and values that underlie one’s actions; and to negotiate values, principles, goals, and targets, in a context of conflicts of interest and trade-offs, uncertain knowledge and contradictions. Advanced Beginner

Anticipatory

The ability to understand and evaluate multiple scenarios for the future – possible, probable and desirable; to create one’s own visions for the future; to apply the precautionary principle; to assess the consequences of actions; and to deal with risks and changes. Novice

Digital Literacy and Judgement

The ability to access, evaluate, create and communicate information in digital environments; to engage critically, ethically and responsibly with digital technologies and digital information; to understand their opportunities, limitations, risks and impact on individual’s digital identities; and to exercise informed judgement in digital participation and decision-making. Competent

AI Literacy & Agency

The ability to understand, critically evaluate and responsibly engage with artificial intelligence; to recognise how AI systems are shaped by human values; to assess their ethical, social and environmental implications; and to exercise human judgement, agency and accountability in AI-related contexts. Novice

Wellbeing

Wellbeing is having the resources and skills to meet life's challenges, including attributes such as personal development skills, resilience, stress management, strengths, lifestyle skills, nutrition, physical activity, sleep, alcohol/substance use, academic skills, time management, goal setting, interpersonal skills, group work, communication. Not addressed

The United Nations identified seventeen Sustainable Development Goals (SDGs) as core to the 2030 Agenda for Sustainable Development, and UCD contributes in general to SDG 4 Quality Education. Further SDGs explored within this module if relevant are listed below. A scale of 1 - 5 indicates the extent to which the SDG is covered.


 

Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

53

Lectures

17

Practical

35

Online Learning

20

Total

125


Approaches to Teaching and Learning:
A mixture of online learning, with lectures and practical sessions

Requirements, Exclusions and Recommendations
Learning Recommendations:

Basic computer literacy (e.g. Excel and Word).


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade Component repeat (in-module) Offered
Exam (In-person): Final 2hr in-person exam on data analysis and experimental design Week 6 Graded No
60
No
Quizzes/Short Exercises: Practical exercises Week 2, Week 4 Pass/Fail Grade Scale No
20
No
Quizzes/Short Exercises: Online test Week 6 Alternative linear conversion grade scale 40% No
20
No

As part of UCD's student support, under the Additional Consideration policy, extensions may be available for the following assessments in the module: Assignment (including essay/poster), Portfolio, Reflective Assignment, Report(s), and Individual Project.


Carry forward of passed components
Yes
 

Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Online automated feedback

How will my Feedback be Delivered?

Not yet recorded.

Beckerman, Childs and Petchey (2017) Getting started with R : an introduction for biologists (Oxford University Press, Oxford) [electronic resource] http://library.ucd.ie/iii/encore/record/C__Rb2147070

Crawley (2015) Statistics : an introduction using R (John Wiley & Sons, Ltd, London) [electronic resource] http://library.ucd.ie/iii/encore/record/C__Rb2103637

Raykov and Marcoulides (2013) Basic statistics : an introduction with R (Rowman & Littlefield Publishers, Inc., Plymouth). [electronic resource] http://library.ucd.ie/iii/encore/record/C__Rb1961859

Barnard, Gilbert and McGregor (2011) Asking questions in biology: a guide to hypothesis testing, experimental design and presentation in practical work and research projects (Pearson) [electronic resource] http://library.ucd.ie/iii/encore/record/C__Rb1880444

Ruxton and Colegrave (2016) Experimental design for the life sciences (Oxford University Press, Oxford)

Underwood AJ (1997) Experiments in ecology: their logical design and interpretation using analysis of variance. (Cambridge University Press, Cambridge).



Name Role
Dr Nicholas Brereton Lecturer / Co-Lecturer
Dr Paul Brooks Lecturer / Co-Lecturer
Assoc Professor Joanna Kacprzyk Lecturer / Co-Lecturer
Dr Marcin Penk Lecturer / Co-Lecturer

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Summer Practical Offering 51 Week(s) - 38, 40 Fri 09:00 - 16:50
Summer Practical Offering 51 Week(s) - 38 Thurs 09:00 - 16:50
Summer Practical Offering 51 Week(s) - 38, 40 Tues 09:00 - 16:50
Summer Practical Offering 51 Week(s) - 38, 40 Wed 09:00 - 16:50