BIOL40390

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:

Approaches to Teaching and Learning:

A mixture of online learning, with lectures and practical sessions

Learning Recommendations:

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

Not applicable to this module.
 

Assessment Strategy  

 

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).