BIOL40390 Quantitative Tools for the Life Sciences

Academic Year 2023/2024

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.

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Curricular information is subject to change

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

Student Effort Hours: 
Student Effort Type Hours
Lectures

17
Practical

35
Autonomous Student Learning

53
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 Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: R script to accompany the online test Unspecified n/a Graded No

10
Examination: Final 2hr exam (open book and online) Week 6 Yes Graded No

50
Class Test: Online Tests Varies over the Trimester n/a Alternative linear conversion grade scale 40% No

40

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

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 Paul Brooks Lecturer / Co-Lecturer
Dr 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
Practical Offering 51 Week(s) - 38 Thurs 09:00 - 16:50
Practical Offering 51 Week(s) - 38, 40 Tues 09:00 - 16:50
Practical Offering 51 Week(s) - 38, 40 Wed 09:00 - 16:50
Summer