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Advanced experimental design and statistical techniques for biologists. This course is essential for all students considering postgraduate study in biological sciences.
Successful completion of BIOL209 is a pre-requisite for BIOL309, as the concepts coveredhere lead on directly from those developed in the previous semester. BIOL309 is essential for all students who intend to pursue postgraduate studies or go on to a career in any branch of biological research.The aim of BIOL309 is to build on the concepts developed in BIOL209 to provide training in the use of advanced statistical techniques and in the design and analysis of biological experiments. The biological focus applies both to the choice of relevant methods and the specific examples discussed. The examples will cover a wide range of biology, from biochemistry to ecology, although you should not expect every topic to be illustrated with an example from your specific area of interest in biology. Note that one goal of the course is to prepare students for postgraduate research programmes and jobs in research organisations, and this affects the choice of course content and style.The course covers data analysis, and emphases how familiar tests such as analysis of varianceand linear regression can be extended to provide a flexible suite of techniques which can be applied to a variety of situations. This knowledge will be applied to the design of experiments,covering concepts such as replication, power and repeated measures. An experiment can be designed properly only on the basis of knowledge of the statistical test that will eventually be required. This emphasis on the need to consider data analysis as an integral part of the experimental design process means that topics will build on one another in sequence.
By the end of this course, you should have achieved the following:1. A clear understanding of a wide range of statistical tests, including analysis of variance, linear regression, non-parametric tests and generalised linear models;2. Proficiency in the transcription and manipulation of data statistical packages;3. A solid understanding of experimental design;4. Proficiency in the analysis of a wide range of biological data.Transferable Skills Register:The ability to phrase statistically rigorous, biologically interesting hypothesesThe ability to identify the best experimental design to test specific biological questionsProficiency with a diverse array of statistical tests and data manipulations in the Rprogramming environmentThe ability to interpret statistical results presented in scientific papersThe ability to communicate the biological meaning of statistical tests.
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
BIOL209 or other statistical background as determined by the Head of School. PSYC206 cannot be used as a prerequisite.
Jason Tylianakis
Ian Dickie
Crawley, Michael J; Statistics : an introduction using R ; Second edition; John Wiley & Sons, Inc, 2014.
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Domestic fee $865.00
International fee $3,788.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see School of Biological Sciences .