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Lismore
National Marine Science Centre Coffs Harbour
Online

Unit description

Data management and analysis are essential tools for scientists. This unit provides students with basic skills in data management, illustration, analysis, and interpretation that will be foundational for careers in science and science-related disciplines. The unit will examine different types of data and how to compare and present them in a scientific manner. It covers introductory-level analyses such as t-tests, ANOVA, correlation and regression, and Chi-square tests. Emphasis is placed on matching data with appropriate statistical tests to provide students with knowledge on how to answer simple scientific hypotheses. The unit also gives an overview of experimental designs and sampling strategies for data collection that can be applied across disciplines.

Unit content

1. Scientific measurements and data

2. Data management

3. Measures for summarising and describing data

4. Statistically comparing data between two groups

5. Statistically comparing more than two groups of data

6. Analysing relationships: correlation and regression

7. Analysing categorical data

8. Experimental and survey designs

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:
1understand and calculate descriptive statistics for a variety of scientific data types
2apply data management skills to organise, analyse and display data
3identify appropriate statistical analyses to test hypotheses and perform basic statistical analyses
4present and interpret results of statistical analyses in a professional manner.

On completion of this unit, students should be able to:

  1. understand and calculate descriptive statistics for a variety of scientific data types
  2. apply data management skills to organise, analyse and display data
  3. identify appropriate statistical analyses to test hypotheses and perform basic statistical analyses
  4. present and interpret results of statistical analyses in a professional manner.

Prescribed texts

  • There are compulsory readings for this unit. See MySCU (http://learn.scu.edu.au) and the Readings in Blackboard for details. If you can get a copy of the optional text, it is as follows:: Ennos, R & Johnson, M, 2018, Statistical and Data Handling Skills in Biology, 4th edn, Pearson, Harlow, UK. ISBN: 9781292086033.
Prescribed texts may change in future teaching periods.

Teaching and assessment

Teaching method
Tutorial on-site 2.5 hrs (12 weeks)
Lecture online 3 hrs (12 weeks)
Assessment
Report30%
Report30%
Exam: open book40%

Teaching method
Tutorial on-site 2.5 hrs (12 weeks)
Lecture on-site 3 hrs (12 weeks)
Assessment
Report30%
Report30%
Exam: open book40%

Teaching method
Tutorial online 2.5 hrs (12 weeks)
Lecture online 3 hrs (12 weeks)
Assessment
Report30%
Report30%
Exam: open book40%
Notice

Intensive offerings may or may not be scheduled in every teaching period. Please refer to the timetable for further details.

Southern Cross University employs different teaching methods within units to provide students with the flexibility to choose the mode of learning that best suits them. SCU academics strive to use the latest approaches and, as a result, the learning modes and materials may change. The most current information regarding a unit will be provided to enrolled students at the beginning of the teaching period.

Fee information

Domestic

Commonwealth Supported courses
For information regarding Student Contribution Amounts please visit the Student Contribution Amounts.

Fee paying courses
For postgraduate or undergraduate full fee paying courses please check Domestic Postgraduate Fees OR Domestic Undergraduate Fees

International

Please check the international course and fee list to determine the relevant fees.

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