The course "Environmental and Ecological Statistics" explores statistical techniques and models used to tackle real-world challenges in environmental and ecological sciences. Students will learn how to analyse complex data sets derived from environmental and ecological studies, understand spatial and temporal variability, and apply models to describe the state of the environment and inform policy decisions. This course addresses the growing demand for specialists who can tackle critical global environmental issues through data visualization, analysis and interpretation. It meets the needs of diverse stakeholders, including government agencies, environmental consultancies, conservation organizations, and academic institutions, which require professionals skilled in cutting-edge techniques to address pressing environmental and ecological challenges. Students will gain graduate attributes such as critical thinking, technical expertise, and communication skills, equipping them to contribute effectively to interdisciplinary teams working on conservation, sustainable resource management, and policy-making.

Lectures: 2 hours per week

Tutorials: 1 hour fortnightly

Practical: 2 hours three times throughout the semester

STATS4009 Environmental and Ecological Statistics

Courses prescribed in the Master's programme to which the student has been admitted.

Written Exam (65%) - Degree exam in the exam diet

Group Report (25%) - Group project running throughout the semester resulting in a group report

Set Exercise (10%) - For example, presenting a critical review of published research

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below.

Group-based projects will not be available for reassessment due to the inherent nature of the assessment. However, the group project weighs only 25% of the total grade. Therefore, the weight of the group project aligns with the permitted limit for non-reassessable assessments (25%). The remaining 75% of the course's summative assessment will still be available for reassessment

(1) To provide students with the statistical knowledge and technical skills to understand and analyse complex environmental and ecological phenomena that, due to the growing concerns about the global environmental crisis, have become essential for effective conservation, sustainable resource management, and informed policy-making.

(2) To equip students with the skills to interpret ecological and environmental data, work collaboratively in teams, and apply statistical methods to key challenges in Environmental Science, preparing them for careers in consulting, research, and policy

(3) To introduce advanced statistical methods developed for real-world environmental and ecological problems, addressing the shortage of specialized training in these fields

By the end of this course students will be able to:

1. Identify quality and uncertainty in environmental and ecological datasets, including key sources of bias and their potential impact on analysis and interpretation.

2. Formulate statistical analyses on complex environmental and ecological phenomena in space and time using modern methods that address challenges such as variability, uncertainty, and large-scale data integration.

3. Demonstrate the ability to communicate complex ecological and environmental analyses effectively to technical and non-technical audiences

4. Critique the methods, data analysis techniques, evidence, and validity of claims presented in scientific papers and environmental statements from both academic and popular sources

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.