Mathematical Statistics
Get a solid education in one of the oldest sciences, with new applications in a growing number of areas in natural and social sciences as well as business. Learn how to understand and solve problems using proofs and logical thinking. Mathematical knowledge has many practical applications, like developing machine learning and artificial intelligence.
Here you can study various areas of mathematics like algebra, geometry, analysis and logic but also applied mathematics. One large and growing application is within mathematical statistics, the new data science and the handling of “Big Data”.
Get deeper insights in areas like cryptography and the mathematical analysis that helps building up models in physics, chemistry, biology, economy etc.
You will get training in how to draw up and modify problems and to solve them with rigorous mathematical arguments. An education in mathematics will give you an understanding of the structure behind all the usable formulas and equations.
Mathematics and mathematical statistics can be studied at both first cycle and second cycle level. In second cycle studies we also offer some courses in insurance mathematics.
It is a great advantage to combine studies in mathematics/mathematical statistics with courses in computer science, many offered by the same department. In that way you will master the most modern tools and get training in the handling and analysis of real data.
You can also combine your studies with courses in science, economy or other areas of interest.
If you would like to study a mathematical area in greater depth and get into research, there are PhD studies given in Mathematics, Mathematical Statistics and Insurance Mathematics.
Career opportunities
Mathematical education is applicable in all fields where advanced mathematical methods are used. Examples include numerical calculations in technology and natural sciences, estimation of probability, price setting in the financial sector, risk analysis and the development of algorithms used to ensure secure transfer of data, and the development of machine learning algorithms.
Alumni from the Department of Mathematics are employed in advanced positions in various parts of industry and in the academic sector.
Courses and programmes
At Stockholm University, you can study mathematical statistics as individual courses at second cycle or by entering our master’s programme. First circle courses are in general only offered in Swedish.
Bachelor's programme

Bachelor's Programme in Mathematics and Economics
NMAEK, Programme, First level , Mathematics , Mathematical Statistics

Bachelor's Programme in Mathematics
NMATK, Programme, First level , Mathematics , Mathematical Statistics

Bachelor's Programme in Mathematics and Computer Science
NMDVK, Programme, First level , Computer Science , Mathematics , Mathematical Statistics


Master's programme

Course at bachelor's level

Mathematical Statistics, Degree Project
MT6001, Course, First level , Mathematical Statistics

Probability and Statistics for Teachers
MT1011, Course, First level , Mathematical Statistics

Stochastic Processes and Simulation I
MT4002, Course, First level , Mathematical Statistics  Held every spring

Probability Theory II
MT5002, Course, First level , Mathematical Statistics

Introduction to Finance Mathematics
MT5009, Course, First level , Mathematical Statistics

Basic Insurance Mathematics
MT5011, Course, First level , Mathematical Statistics

Stochastic Processes and Simulation II
MT5012, Course, First level , Mathematical Statistics

Mathematical statistics, Degree Project
MT6010, Course, First level , Mathematical Statistics

Theory of Statistical Inference
MT5003, Course, First level , Mathematical Statistics

Categorical Data Analysis
MT5006, Course, First level , Mathematical Statistics

Probability Theory I
MT3001, Course, First level , Mathematical Statistics

Statistical Analysis
MT4001, Course, First level , Mathematical Statistics

Linear Statistical Models
MT5001, Course, First level , Mathematical Statistics

Statistical Data Processing
MT5013, Course, First level , Mathematical Statistics

Econometric methods
MT5014, Course, First level , Mathematical Statistics


Course at master's level

Insurance Mathematics, Degree Project
MT9012, Course, Second level , Mathematical Statistics

Mathematical Statistics, Degree Project
MT9013, Course, Second level , Mathematical Statistics

Insurance Accounting
MT7035, Course, Second level , Mathematical Statistics

Insurance Law for Actuaries I
MT7017, Course, Second level , Mathematical Statistics

Statistical Models
MT7002, Course, Second level , Mathematical Statistics

Risk models and claims reserving in nonlife insurance
MT7027, Course, Second level , Mathematical Statistics

Statistical Information Theory
MT7037, Course, Second level , Mathematical Statistics

Unsupervised Learning
MT7039, Course, Second level , Mathematical Statistics

Nonlife insurance pricing
MT7028, Course, Second level , Mathematical Statistics

Probability Theory III
MT7001, Course, Second level , Mathematical Statistics

Mathematical Methods in Life Assurance I
MT7012, Course, Second level , Mathematical Statistics

Survival Analysis
MT7006, Course, Second level , Mathematical Statistics

Selected Topics in Probability Theory and Stochastic Processes
MT7031, Course, Second level , Mathematical Statistics

Statistical Learning
MT7038, Course, Second level , Mathematical Statistics

Degree
To get a bachelor’s degree in Mathematics or Mathematical Statistics, you can combine free standing courses or follow a Bachelor’s Programme listed under Education.
To get a Master’s degree in Mathematics or Mathematical statistics, you can combine free standing courses or follow a Master’s Programme listed under Education.
Research
Research is conducted in a wide variety of subfields of pure and applied mathematics as well as statistics. Some of our researchers are active in abstract subjects like logic and topology while others work in areas of immediate societal interest such as climate modeling and insurance.
Some mathematical disciplines, including spectral theory, random processes and number theory, are driven both by mathematical interest and by potential applications in theoretical physics, analysis of financial markets, and cyber security.