Module: Environmental Data Analysis

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Environmental Data Analysis
Module Code	ENS1022
Faculty	Humanities & Social Sciences	School	History & Geography
NFQ level	8	Credit Rating	7.5

Description

Environmental science increasingly depends on the ability to collect, analyse, and interpret data from diverse sources. This module introduces core techniques for organising and analysing environmental data through descriptive and inferential statistics, and for visualising data using Geographical Information Systems (GIS). Fieldwork and practical exercises provide the foundation for learning. Students will collect and process environmental datasets, apply statistical and spatial analysis, and work collaboratively to investigate environmental questions. Emphasis is placed on clear communication of results through tables, graphs, maps, and structured reports. By the end of the module, students will be able to analyse, interpret, and present environmental data using appropriate statistical and visual techniques.

Learning Outcomes

1. Classify data types, apply descriptive statistics, select appropriate sampling methods, and interpret findings using basic inferential statistics.
2. Apply research design principles and sampling methods to collect reliable data suited to research questions.
3. Apply spreadsheets, statistical software, and GIS tools to organise, manage, analyse, visualise, and describe environmental data.
4. Present environmental data clearly using appropriate statistics, tables, graphs, and maps.
5. Collaborate in a group to collect, process, and present environmental data.
6. Analyse, interpret, and synthesise environmental data in a structured written report.

*Type*	*Hours*	*Description*
Workload	Full time hours per semester
Assessment Feedback	187.5	No Description
Total Workload: 187.5

Section Breakdown
CRN	11895	Part of Term	Semester 1
Coursework	100%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	N
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Niamh Cullen	Module Teacher

Type	Description	% of total	Assessment Date
Assessment Breakdown

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Indicative Reading List

Books:

Simon J Dadson: 2017, Statistical analysis of geographical data: An introduction., Wiley and Sons,

Articles:
None

Other Resources

None