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Statistical Science for the Life and Behavioural Sciences

Master

Year 1

Course EC Semester 1 Semester 2
Introduction to Life and Behavioral Sciences 3
Linear & generalized linear models and linear algebra 9
Mathematics for statisticians 3
Statistical computing with R 6
Statistics and probability 9
Mixed and longitudinal modeling 6
Study designs in the Life and Behavioral Sciences 6
Bayesian Statistics 6
Multivariate analysis and multidimensional data analysis 6
Survey Methodology 6
Survival analysis 6

Year 2

Course EC Semester 1 Semester 2
High-dimensional data analysis 6
Psychometrics and SEM 6
Statistical Consulting (Statistical Science) 5
Statistical genetics 6
Statistical learning 6
EMOS Core Module 12
Internship and Master Thesis 34
Internship 10
Master Thesis 24

The master programme Statistical Science for the Life Sciences and Behavioural Sciences is organised jointly by groups at different institutes and universities:

• Mathematical Institute, Leiden University

• Faculty of Social and Behavioural Sciences, Leiden University

• Department of Biomedical Data Sciences, Leiden University Medical Center

• Biometris – Applied Statistics, Wageningen University and Research centre

Together these institutes have expertise in a wide area of statistical science and its applications, both practical and theoretical. Many of the scientific staff members are involved in other educational tasks, or are specialised in research and statistical consultation.

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.

Statistics for the life sciences is almost synonymous with biostatistics. It incorporates quantitative modelling 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 given 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. Programme

The Statistical Science programme provides students with a thorough introduction to the general philosophy and methodology of statistical modelling and data analysis. Students also gain knowledge of statistical methods and research designs as used in a broad range of empirical research, and practical skills such as statistical programming, statistical consultation, and written and oral communication of research results.

The nominal duration of the programme will be two years (120 ECTS). The study time may be substantially reduced for students with particular prior knowledge.

Statistical Science graduates’ skills and competences

The Statistical Science programme provides the students with a thorough knowledge of

• Statistical methods and research designs as used in a broad range of empirical research

• Practical skills such as statistical programming, statistical consultation, and written and oral communication of research results.

The graduates will be able to carry out research in the field of quantitative methods for the medical and life sciences and/or the behavioural sciences. They will be able to advise substantive researchers on methodological and statistical issues, and many of them will be expected to continue in a PhD programme. Whether more attracted to the medical or to the behavioural direction, the successful student will gain a thorough understanding of statistical models, their implementation and their interpretation, and develop the ability to invent new models and techniques when needed. Graduates will thus qualify for jobs in a wide range of areas, such as academic medical hospitals, many types of industry (pharmaceutical, agricultural, food, life science in general, oil, etc.), research institutes, financial institutions, government statistics bureaus, educational services (CITO), marketing bureaus. In view of the emphasis on statistics as a science, rather than as merely a collection of techniques, many graduates will qualify for a PhD programme as well.