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AESC40180

Academic Year 2024/2025

Data Analysis for Biologists (AESC40180)

Subject:
Agricultural&Environmental Sci
College:
Health & Agricultural Sciences
School:
Agriculture & Food Science
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Assoc Professor Barry John McMahon
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

The core principles required in the quantitative analysis, interpretation and communication of ecological data are described. Emphasis is placed on the use of generalized linear models to evaluate relationships between univariate response variables (e.g. specific population abundance) and ecological drivers (e.g. management factors), and on the use of multivariate methods to evaluate and compare the influence of environmental factors on plant and animal communities. In addition, generalized linear mixed models usage and applications will be covered. Empirical datasets are provided and worked examples used in classes that will not assume significant levels of prior knowledge. Emphasis will be placed on how the described methods are used for practical management. All practicals are conducted through R.

About this Module

Learning Outcomes:

1. Describe the differences and objectives in univariate and multivariate data
2. Analyze data and interpret what the results signify
3. prepare and present an analysis of their own data producing outputs suitable for publication both in numerical and graphical form
4. Become familiar with running models through R
5. Appraise similar methods in the literature

Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

64
Lectures

12
Computer Aided Lab

24
Total

100

Approaches to Teaching and Learning:
Using delivered course content material as basic level of knowledge, in class problems are given to students to use as self assessment markers with feedback provided through discussion. This is achieved through active/task-based learning; peer and group work; lectures; reflective learning.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): End of semester assignment. Week 11 Graded No
100
 No

Carry forward of passed components
No
 

Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Ms Laura Gallego-Lorenzo Tutor

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 09:00 - 09:50
Spring Laboratory Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 10:00 - 11:50
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