Statistics in the Natural Sciences (ENVX3002)
UNIT OF STUDY
This unit of study is designed to introduce students to the analysis of data they may face in their future careers, in particular data that are not well behaved, they may be non-normal, there may be missing observations or they may be correlated in space and time. In the first part, students will learn how to analyse and design experiments based on the general linear model. In the second part, they will learn about the generalisation of the general linear model to accommodate non-normal data with a particular emphasis on the binomial and poisson distributions, in addition to modelling non-linear relationships. In the third part linear mixed models will be introduced which provide the means to analyse datasets that do not meet the assumptions of independent and equal errors, for example data that is correlated in space and time. At the end of this unit, students will have learnt a range of advanced statistical methods and be equipped to apply this knowledge to analyse data that they may encounter in their future studies and careers.
Further unit of study information
2x2 hr workshop/wk, 1x3 hr computer practical/wk
1 × Exam during the Exam period (50%), 5 × Assessment Tasks (5x10%)
-Mead R, Curnow RN, Hasted AM (2002) 'Statistical methods in agriculture and experimental biology.' (Chapman & Hall: Boca Raton).
-Quinn GP, Keough MJ (2002) 'Experimental design and data analysis for biologists.' (Cambridge University Press: Cambridge, UK).
Faculty/department permission required?
Unit of study rules
Prerequisites and assumed knowledge
ENVX2001 or BIOM2001 or STAT2012 or STAT2912 or BIOL2022 or BIOL2922
Study this unit outside a degree
If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student.
If you are from another Australian tertiary institution you may be permitted to underake cross-institutional study in one or more units of study at the University of Sydney.