Statistics and Data Science I, 7.5 credits

Autumn 2024, Half-time, Norrköping

Closed for late application
Semester Autumn 2024
Place of study Norrköping
Pace of study Half-time
Level Second cycle
Teaching form On-Campus
Education Time Day-time
Education Language English
Course offering id LIU-46101
Period 202434 - 202443
Number of Places 2

Specific requirements

  • 180 ECTS credits passed including 90 ECTS credits within one of the following areas humanities, social-, cultural-, behavioural-, natural-, computer-, or engineering-sciences
  • 15 ECTS credits passed in one or several of the following subjects:
    Statistics
    Mathematics
    Computer science
  • English corresponding to the level of English in Swedish upper secondary education (Engelska 6)
    Exemption from Swedish

Selection

Tuition fees

SEK 17600 - NB: Applies only to students from outside the EU, EEA and Switzerland.

If you have questions about the course, contact us

Carl Nordlund, course director

Madelene Töpfer, course administrator

Jonas Johansson, study adviser

Course syllabus

Statistics and Data Science I, 7.5 credits

Autumn 2025, Half-time, Norrköping

Semester Autumn 2025
Place of study Norrköping
Pace of study Half-time
Level Second cycle
Teaching form On-Campus
Education Time Day-time
Education Language English
Course offering id LIU-46101
Period 202534 - 202543
Number of Places 2

Specific requirements

  • 180 ECTS credits passed including 90 ECTS credits within one of the following areas humanities, social-, cultural-, behavioural-, natural-, computer-, or engineering-sciences
  • 15 ECTS credits passed in one or several of the following subjects:
    Statistics
    Mathematics
    Computer science
  • English corresponding to the level of English in Swedish upper secondary education (Engelska 6)
    Exemption from Swedish

Selection

Tuition fees

SEK 17600 - NB: Applies only to students from outside the EU, EEA and Switzerland.

If you have questions about the course, contact us

Carl Nordlund, course director

Madelene Töpfer, course administrator

Jonas Johansson, study adviser

Course syllabus

This course provides an overview of key results in probability and statistics relevant for social research and introduces programming tools for statistical analysis. Major probability distributions, including the binomial, normal, exponential, and Poisson distributions, used in social science research are introduced and their properties and applications are explored in intensive computer labs. Statistical software is used to simulate from these distributions. Computational methods, including Monte Carlo simulation, are used to explore key theorems under various conditions. Hypothesis tests for parameters and statistics related to common univariate distributions are introduced, and computational alternatives (e.g., bootstrapping, permutation tests) are considered.