Statistics are used daily in all areas of society and statistics as a science involves the study of methods used to draw conclusions about difficult problems. Examples of questions that can be answered with statistical methods are: What is the impact of new medical treatments and how strong is their effect? How many people are unemployed? What actions affect unemployment and to what extent? Will the repo rate go up or down within a certain time period?
As a statistician you usually work closely with subject specialists in a variety of areas and the statisticians role is to have knowledge of how data are collected, analysed and interpreted.
Work as a statistician also includes method development, which is to improve existing or develop new methods. With a masters degree in Statistics, you get a good base to work with the above tasks.
Statistics is both a formal science and a practical approach, and both aspects are taken into account in the programme. The goal of the Master Programme in Statistics is to prepare students well for skilled jobs, and for continuing graduate studies.
Statisticians are in demand on the labour market and through its methodological breadth, the Master Programme in Statistics offers students very good opportunities for employment in a variety of areas, both private and public. Amongst private employers, positions for statisticians are often found in the financial sector (banks, insurance, etc.), biomedical companies, research companies, opinion polling organisations and associations, while qualified statisticians in the public sector often work as analysts and investigators.
It is also common for statisticians to work at research institutions. The education also provides eligibility for Ph.D.studies in Statistics.
The programme leads to a Master of Social Science (120 credits) with Statistics as the main field of study.
After one year of study it may also be possible to obtain a Master of Social Science (60 credits).
The programme begins with courses in Probability and Inference. These will consolidate and deepen the theoretical understanding of randomness and how to draw conclusions from data that contains random variation.
For students who desire a more theoretical training and are interested in methodology, the programme provides the opportunity to further deepen the theoretical knowledge through additional courses, for example, Asymptotic Theory and Bayesian Methods.
The theory oriented courses will provide a strong foundation in basic statistical theory that is later used in the more applied courses.
In the applied courses, the student will learn how to use statistical techniques to deal with important real world problems. Obtained skills are collecting, processing and analysing data, interpreting and presenting results and empirical models.
Since the courses span over several areas such as biostatistics, econometrics, and structural equation models, there are numerous opportunities to specialize, depending on your interests.
Econometrics, Epidemiology, Generalized Linear Models, Non-parametric Methods, Planning and Analysis of Clinical Trials, Statistical Programming in Structural Equation Models, Survival Analysis, and Repeated Measurements.
For example, the course Econometrics deals with statistical methods for the analysis of economic data and the estimation of theoretical economic models. Based on this analysis, relevant questions can be answered, e.g. what is the effect of a tax change, what is the return on education, etc.
In the course Survival Analysis, you will learn how to estimate the effect of a new medicine on survival time. These methods are moreover the same as those used to study the effects of labour market policies with regard to the time period an individual is unemployed. A good example of how useful statistical methods are in general!
Uppsala University provides several different scholarships for students. The scholarships cover exclusively the tuition fees for courses within the programme, i e 30 credits per semester.
Read more about scholarships on www.uu.se/scholarships.