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SC5502 - Design and Analyses in Ecological Studies

Credit points: 3
Year: 2023
Student Contribution Band: Band 1
Administered by: College of Science and Engineering

This subject focusses on collection and statistical analysis of ecological data, providing insight in the mechanisms and consequences of theories in ecology. Students are expected to extend their skills and demonstrate their understanding of: the types of data that might be generated, some of the analyses that are available for particular purposes, the assumptions that underpin those analyses, how to interpret and communicate the end product of the analyses, and the need for a critical and informed approach to statistical analysis. The subject is designed for postgraduate students whose future professional activities are likely to require an understanding of the design and analysis of ecological studies and the interpretation of the output from statistical software in a biological context. In particular, those students who intend to move into honours or graduate studies (Masters or PhD), and those who intend to work as professional scientists.

Learning Outcomes

  • select and apply appropriate statistical analyses for a range of sampling regimes and data types, and subsequently interpret the results in an ecological context;
  • problem solve complex issues in the acquisition, analysis, interpretation and communication of scientific research;
  • initiate, analyse and communicate field based research projects in ecology, thereby demonstrating competency in scientific research.

Subject Assessment

  • Written > Examination (centrally administered) - (50%) - Individual
  • Oral > Presentation 1 - (30%) - Group
  • Written assignment - (20%) - Individual.
Assumed
Knowledge:
Students enrolling in this subject should have an undergraduate degree in a relevant discipline or have acquired equivalent knowledge through other study. They should have an excellent understanding of ecological principles and statistics, and have successfully completed a basic univariate statistics course at university level. Familiarity with R is assumed.
Inadmissible
Subject
Combinations:
MB5300

Availabilities

Cairns, Study Period 2, Internal
Census Date 24-Aug-2023
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 24 hours workshops
  • 2 hours seminars
  • 24 hours online activity
  • 12 hours online Seminars
  • assessment and self-directed study

Townsville, Study Period 2, Internal
Census Date 24-Aug-2023
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 24 hours workshops
  • 2 hours seminars
  • 24 hours online activity
  • 12 hours online Seminars
  • assessment and self-directed study

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.