Statistical Science for the Life and Behavioural Sciences
| Specialisatie van: | Mathematics |
|---|---|
| Graad: | Master of Science in Mathematics |
| Onderwijsvorm: | Voltijd |
| Duur: | 2 jaar |
| Start: | Flexibel, maar bij voorkeur in september of februari |
| Taal: | Engels |
| Vestigingsplaats: | Leiden |
| Croho/isatcode: | 66980 |
De masterspecialisatie Statistical Science for the Life Sciences and Behavioural Sciences wordt gezamenlijk verzorgd door een groep verschillende instituten en universiteiten:
- Mathematisch Instituut, Universiteit Leiden
- Faculteit der Sociale Wetenschappen, Universiteit Leiden
- Department Medische statistiek en bioinformatica, Leids Universitair Medisch Centrum
- Department Wiskunde, VU Amsterdam
- Biometris – Toegepaste statistiek, Wageningen Universiteit en Researchcentrum
Deze instituten hebben gezamenlijk een uitgebreide expertise in de statistiek in haar volle breedte, zowel praktisch als theoretisch. Veel docenten zijn betrokken bij andere onderwijsprojecten, of zijn gespecialiseerd in onderzoek of statistische consultancy aan overheid en bedrijfsleven.
Statistics is the art of drawing conclusions about phenomena in which chance plays a role. The randomness may arise through a variety of reasons: the intrinsic random nature of a phenomenon, unavoidable noise in an experiment, conscious randomisation of experimental or measurement units, or as a best approximation to reality. The chance phenomena occur in a broad range of situations. This has rendered statistical science a highly multidisciplinary undertaking, but with a core body of concepts and methods that are common to the diverse applications.
Statistical Science for the Life Sciences
Statistics for the life sciences is almost synonymous with biostatistics. It incorporates quantitative modeling and methods of data analysis for clinical and epidemiological research (e.g. survival analysis), which in the past twenty years have become indispensable in medical research. It also includes statistical methods used in genetic research and genomics, which have a classical foundation (for instance in the work of Fisher, the founding father of statistics), but are rapidly developing in answer to present-day opportunities provided by data from new experimental platforms, such as micro-arrays or whole-genome scans.
The programme is targeted both at human and at plant or animal genetics. In the coming years, systems biology will make similar demands for new statistical methodology, and the analysis of medical images will increase in importance, both in research and in clinical applications.
Statistical Science for the Behavioural Sciences
It is no exaggeration to say that all empirical research in the presentday social and behavioural sciences relies predominantly on statistical analysis. There is a long-standing statistical tradition in educational and psychological testing (psychometrics), and also in survey research, marketing research and quantitative demographics (sociometrics).
Similar sub-domains that have emerged more recently are the quantitative study of the development of science and technology (scientometrics and bibliometrics), the quantitative study of stylistic forms and patterns in the use of language (stylometrics), the quantitative study of taste and smell (sensometrics), the quantitative study of history (cliometrics), and the empirical approach to the law (jurimetrics). The common use of the term ‘metrics’ here illustrates the important role of measurement problems in these fields.
Special attention must also be given to application in cognitive science (fMRI data) and forensic statistics (DNA data), while biological psychology is also between the life and behavioural sciences.
