What is Statistics?
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) that 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, one of the founding fathers of statistics), but are rapidly developing in answer to present-day opportunities provided by data from new experimental platforms, such as micro-arrays and whole-genome scans.
The program is targeted at human genetics as well as plant and animal genetics. Areas like systems biology 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 present day 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 (sociometric).
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.
Although some statisticians would argue that Data Science = Statistics, we prefer the point of view that there is quite an overlap between the two, but they are not identical. We would say that Data Science is a combination of Statistical Science and Computer Science, and there should be no Data Science without Statistics, but also no Data Science without Computer Science. That is why we offer a specialization of Statistical Science called Data Science, in collaboration with the Leiden Institute of Advanced Computer Science (LIACS). Students in this specialization follow the mandatory courses in the basic Statistical Science program, and use the ECTS to be spend on elective courses in the program to follow necessary courses in Computer Science.
It is extremely convenient that Statistical Science and Computer Science are located in the very same building in Leiden (the Snellius Institute). Through this cooperation, Leiden University aims to fill a growing job market demand by offering its students a unique combination of theoretical and practical tools stepping into the promising area of Data Science.