BIOL30030 Working with Biological Data

Academic Year 2021/2022

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

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

Students will require their own laptops.

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Curricular information is subject to change

Learning Outcomes:

Learning Outcomes:
1. Organise and manipulate data on a computer;
2. Design a biological / environmental experiment, taking due account of independence, allocation of replicates and controls;
3. Fit and validate a statistical model to biological data;
4. Test a null-hypothesis using fitted statistical models;
4. Accurately communicate data using graphs, tables and written text;
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 (open science)
• Spreadsheet (Excel), R statistical language and general computer skills

Student Effort Hours: 
Student Effort Type Hours
Lectures

5

Practical

19

Autonomous Student Learning

93

Online Learning

8

Total

125

Approaches to Teaching and Learning:
A mixture of lectures, practicals and online learning 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Continuous Assessment: Working with R Test Throughout the Trimester n/a Alternative linear conversion grade scale 40% No

40

Examination: Final Exam (open book) 2 hour End of Trimester Exam Yes Graded No

50

Assignment: R Script corresponding to online test Throughout the Trimester n/a Graded No

10


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
Professor Tasman Crowe Lecturer / Co-Lecturer
Dr John Finarelli Lecturer / Co-Lecturer
Willson Gaul Lecturer / Co-Lecturer
Veronica Farrugia Drakard Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Spring
     
Workshop Offering 1 Week(s) - 19, 20, 21, 22, 23, 24, 25, 28, 29, 30, 31, 32 Mon 10:00 - 10:50
Workshop Offering 1 Week(s) - 19, 20, 21, 22, 23, 24, 25, 28, 29, 30, 31, 32 Tues 12:00 - 12:50
Spring