Data Analysis in Science (1809.8)
|Level:||Level 1 - Undergraduate Introductory Unit|
|HECS Bands:||2, 4|
|Faculty:||Faculty of Science and Technology|
|Discipline:||Academic Program Area - Science|
UC - Canberra, Bruce
Year Teaching Period Convener Mode of Delivery 2020 Semester 2 DR Adrian DUSTING (Ph: +61 2 62015941 ) ON-CAMPUS
Possible changes to your unit's learning activities and assessment items
As a result of the Australian Government's directives requiring physical distancing and restrictions on movement because of the COVID-19 pandemic, you may find that learning activities and/or assessment items in some units you are studying have changed. These changes will not be updated in the published Unit Outline but will be communicated to you via your unit’s UCLearn(Canvas) teaching site. The new learning activities and/or assessment items will continue to meet the unit's learning outcomes, as described in the Unit Outline.
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- Semester 2, 2019, ON-CAMPUS, BRUCE (190229) - View
- Semester 2, 2018, ON-CAMPUS, BRUCE (181488) - View
- Semester 2, 2017, ON-CAMPUS, BRUCE (166000) - View
- Semester 2, 2016, ON-CAMPUS, BRUCE (149803) - View
- Semester 2, 2015, ON-CAMPUS, BRUCE (139231) - View
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This subject gives students an understanding of the application of elementary and numerical techniques used in natural sciences assessment and management. It also introduces students to the concepts and techniques used in the modelling of interactive systems.
On successful completion of this unit, students will be able to:
1. Recognise essential elements of their research system and understand particular principles of simple system analysis;
2. Design and conduct an experiment within a quality control and assurance framework;
3. Collect and manipulate data that are both of a numerical and non-numerical character;
4. Comprehend, apply and interpret the results of standard data analysis and statistical methods including descriptive statistics, parametric and non-parametric hypothesis testing, linear regression, and simple analyses of variance and be able to express these effectively in a written environment;
5. Use standard statistical packages such as SPSS as well as Excel to prepare, manipulate and process data; and
6. Integrate quantitative information with statistical outcomes towards developing an understanding of a research topic.
1 hour lecture, 3 hours tutorial per week.
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6540 Introduction to Statistics,
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