Syllabus for Statistical Methods in Physics

Statistiska metoder i fysiken


  • 5 credits
  • Course code: 1FA357
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Physics A1N
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2010-03-18
  • Established by:
  • Revised: 2021-03-26
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Autumn 2022
  • Entry requirements: 120 credits with basic statistics and 60 credits in physics. Proficiency in English equivalent to the Swedish upper secondary course English 6.
  • Responsible department: Department of Physics and Astronomy

Learning outcomes

On completion of the course, the student should be able to:

  • account for the difference between Bayesian and frequentistic statistics
  • compare different data,judge the degree of compatibility and correctly treat uncertainties
  • carry out function minimisation, both analytically and numerically
  • establish confidence intervals
  • estimate parameters using established methods
  • perform hypothesis testing and relate the result to probability
  • utilize common software tools, including Monte Carlo generators, for statistical analysis
  • perform an unfolding of a function from data


Practical skills with statistical methods that are used in physics. Bayesian vs. frequentistic statistics, Uncertainties, Probability distributions, Expectation value and variance. Parameter estimation: Method of Moments, Maximum-Likelihood, Least Squares. Hypothesis testing: Chi Square, Signal vs. Background, Kolmogorov-Smirnov test. Function minimisation with constraints. Basic orientation on common software tools, numerical minimizing procedures, simple Monte Carlo generators and unfolding of functions from data.


Online lectures, IRL lectures with focus on problem solving. Workshops.


Hand-in exercises with oral presentations at the workshop. Active participation at lectures and workshops.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Reading list

Reading list

Applies from: Autumn 2022

Some titles may be available electronically through the University library.

  • Bevington, Philip R.; Robinson, D. Keith Data reduction and error analysis for the physical sciences

    3. ed.: Boston: McGraw-Hill, cop. 2003

    Find in the library


Last modified: 2022-04-26