An indispensable attribute of an effective scientific researcher is the ability to collect, analyse and interpret data. Central to this process is the ability to create hypotheses and test these by using rigorous experimental designs. This modular unit of study will introduce the key concepts of experimental design and data analysis. Specifically, you will learn to formulate experimental aims to test a specific hypothesis. You will develop the skills and understanding required to design a rigorous scientific experiment, including an understanding of concepts such as controls, replicates, sample size, dependent and independent variables and good research practice (e. g. blinding, randomisation). By completing this unit you will develop the knowledge and skills required to appropriately analyse and interpret data in order to draw conclusions in the context of an advanced research project. From this unit of study, you will emerge with a comprehensive understanding of how to optimise the design and analysis of an experiment to most effectively answer scientific questions.
Unit details and rules
Academic unit | Mathematics and Statistics Academic Operations |
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Credit points | 6 |
Prerequisites
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144 credit points of units of study and including a minimum of 24 credit points at the 3000- or 4000-level and 18 credit points of 3000- or 4000-level units from Science Table A. |
Corequisites
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None |
Prohibitions
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ENVX3002 or STAT3X22 or STAT4022 or STAT3X12 |
Assumed knowledge
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Completion of units in quantitative research methods, mathematics or statistical analysis at least at 1000-level. |
Available to study abroad and exchange students | Yes |
Teaching staff
Coordinator | John Ormerod, john.ormerod@sydney.edu.au |
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Lecturer(s) | Floris Van Ogtrop, floris.vanogtrop@sydney.edu.au |