We face an increased flow of information every day. As a qualified statistician, you can analyse this data and find out what is important and what to ignore. The Master's Programme in Statistics offers you a solid foundation in statistical theory and a deeper knowledge of areas such as econometrics, psychometrics and biostatistics. This provides you with the skills to critically analyse and interpret data from various application areas.
The research at the Department of Statistics mainly concerns two fields, econometrics (both micro and time series econometrics) and Structural Equations Modelling (SEM). Within micro econometrics the focus is on causal inference while in time series econometrics, we study macro economic models, in particular analysis of long term relations, i.e. cointegration, and forecasting. SEM deals with the modelling of unobserved (i.e. latent) variables which is popular in psychology and business administration.
We are also interested in analysis of financial data. Many empirical studies indicate that such data are volatile, which means that their degree of fluctuation differs between different time periods. (For example, the volatility is high during periods of financial crisis.) Hence, there is a great need for statistical methods that take this kind of behaviour into account.
Why this programme?
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?
What actions affect unemployment and to what extent?
What are the effects of terrorist attacks on election outcomes?
Problems related to "Big Data", for example, how to understand and target customers, how to understand and optimise business processes, or how to improve sports performance.
As a statistician you usually work closely with subject specialists in a variety of areas and the statistician's 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.
During the programme you can expect to:
be able to interpret, analyse, and critically evaluate results on the basis of scientific and ethical considerations
develop your ability to, critically and creatively, identify and formulate problems of significance for statistical science
Progression in the programme entails a higher level of intellectual maturity and deeper insights into the complexities of the subject. This, together with the ability to integrate knowledge and skills and to independently formulate and solve problems, is demonstrated in your Master's thesis.
Student profile You have a strong foundation in statistics. You might have some practical experience working in the field after taking your Bachelor's degree but not so long so you have forgotten your broad theoretical base and study techniques.
A future PhD education is a possibility you might have thought about and you would value an opportunity to get in closer contact with current research. You also know that experts in statistics are in high demand in many business areas so starting to work right after graduation is also something you are considering. You like to keep your options open for now.
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 comprises four semesters of full-time study and is based on course modules of 7.5 or 15 credits.
During the first three semesters, besides applied courses, core courses in probability theory and statistical inference, and a course in programming are given. Semester four is devoted to a degree project (Master's thesis) worth 30 credits, where the prerequisites are at least 60 credits in Statistics at the advanced level.
If you wish to conclude your studies after one year, you replace coursework worth 15 credits in the second semester with a degree project (Master's thesis). The prerequisites for this thesis are at least 30 credits in Statistics at the advanced level.
Courses within the programme
Semester 1, 2 and 3 Probability Theory Inference Programming
Alongside these courses, more applied courses are offered. Examples of courses: Econometric Theory and Methodology Financial Econometrics Generalised Linear Models Multivariate Analysis Structural Equation Models Survival Analysis Time Series Econometrics
Semester 4 Master's thesis, 30 credits
The Master's Programme in Statistics is an international education and is taught in English. Instruction is mainly in the form of lectures, seminars and tutorials with elements of assignments. Examination of the courses is in the form of written exams, assignments and seminars. The programme is offered in Uppsala.
During the programme you will also have the opportunity to experience a semester of supervised training at a public authority, an organisation or a company that can provide work assignments of value to your selected specialisation and future career plans. The traineeship semester comprises 30 credits.
Statisticians are in demand on the labour market and through its methodological breadth, the Master's Programme in Statistics offer you 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, consulting companies, opinion polling organisations and associations, while qualified statisticians in the public sector often work as analysts and investigators.
Our graduates work at, for example, the National Agency for Education, Statisticon, Universal Music, and Kairos Future. Job titles include statistician, data scientist, and consultant analyst.
It is also common for statisticians to work at research institutions. The qualification also provides eligibility for PhD studies in statistics.
Career support During your whole time as a student UU Careers offers you support and guidance. You have the opportunity to partake in a variety of career activities and events, as well as receive individual career counselling. This service is free of charge for all students at Uppsala University. Read more about UU Careers.
Requirements: Academic requirements A Bachelor's degree, equivalent to a Swedish Kandidatexamen, from an internationally recognised university. Also required is 90 credits in statistics.
Language requirements All applicants need to verify English language proficiency that corresponds to English studies at upper secondary (high school) level in Sweden ("English 6"). This can be done in a number of ways, including through an internationally recognised test such as TOEFL or IELTS, or through previous upper secondary (high school) or university studies. The minimum test scores are:
IELTS: an overall mark of 6.5 and no section below 5.5
TOEFL: Paper-based: Score of 4.5 (scale 1–6) in written test and a total score of 575. Internet-based: Score of 20 (scale 0–30) in written test and a total score of 90
a total appraisal of quantity and quality of previous university studies with emphasis on grades in relevant fields and degree project (if any);
a summary in English (1-2 pages) of a previous degree project (if any); and
a statement of purpose (1-2 pages).
Tuition fee-paying students and non-paying students are admitted on the same grounds but in different selection groups.
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees. Fees cover application and tuition only and do not cover accommodation, academic literature or the general cost of living. Read more about fees.
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