Master of science in statistics
Presentation
A challenge for the future
Professions are becoming increasingly multidisciplinary. It is no longer enough to master only one technological or managerial field, we must know how to combine aspects from several different disciplines in order to manage a coherent body of information and data. The field of statistics plays an important role in this sense because it helps us "to sort out" information and to keep only the essential in order to draw relevant conclusions. The importance of statistical tools becomes clear when one considers the steadily increasing flow of raw data that needs to be processed.
In the financial field, for instance, banks can no longer rely solely on traditional methods. They increasingly depend on statistical forecasting methods. Banks use specific statistical methods such as time series, nonparametric methods and robust techniques.
In economics, statistical tools such as stochastic processes, play an essential role in analyzing social welfare, dynamics in employment, quality of life, and conservation and usage of energy. In the vast field of demographics, statisticians use sophisticated forecasting models to predict population growth.
In industry, companies routinely makes use of experimental designs, another statistical method to test new products or to improve quality control.
Statistics also plays an important role in health fields, especially in epidemiology and medicine. In epidemiology, vaccination programs have been the subject of statistical studies. Here, the aim is to determine population segments most susceptible to a disease, the rate of virus transmission, and the consequences of vaccination. In medicine, clinical trials are particularly useful in comparing various treatments to demonstrate the effectiveness of new medication.
Evidently, statistical methodology and applications are indispensable. Training in statistics must combine experimental, practical and theoretical aspects. The Master's degree in statistics is particularly designed to equip students with these vital skills. The program provides a solid training in statistical theory and applied methods in practical experience. It is catered to both university students and professionals.
Specific strengths
Courses in the MScSTAT program are taught by invited internationally recognized professors and the faculty of the Institute of Statistics (ISTAT). Research interests encompass sampling, estimation, semi/non-parametric methods, multivariate statistics, data mining and complex data analysis. ISTAT maintains a constant and productive collaboration with the Swiss Federal Statistical Office .
Professional Perspectives
The objective of the Master's degree in Statistics is to train students to become independent statisticians ready to enter and operate in the professional environment. More than 200 students have already successfully completed the postgrad program - the precedent of the Master's. Today, many occupy high-ranking positions in various, well-known enterprises and organizations including the Swiss Federal Statistical Office, Phillip Morris and universities.
Admission
Admission is open to candidates in possession of a Bachelor of Science or Bachelor of Economics degree conferred by a Swiss university, or of another university degree considered equivalent. In the latter case, equivalence will be determined by the dean, according to CRUS guidelines.
Candidates in possession of other Bachelor qualifications may also be admitted. If their statistical and mathematical background is judged insufficient, admission may be granted on the condition of completing the lacking theoretical basics during a prepatory year preceeding the MScSTAT. The decision for such conditional acceptance is made by the dean, upon the proposal of the program committee, and according to CRUS guidelines.
Registration for the Master in Statistics is not possible for the academic year 2024-2025
Information : immatriculation@unine.ch
Awarded title
Master of Science in statistics
Master of Science en statistique
Beginning of courses
Automn semester (September)
Credits
90 ECTS during 3 semesters
Language of instruction
English
Place of courses
University of Neuchâtel, Faculty of science
Person in charge of the program
Yves Tillé, professor
Director of the Institute of statistics
University of Neuchâtel