Student Pages
Undergraduate course

Basic Course in Statistics

Teaching semester


Objectives and Content


To give an introduction to probability theory and statistical methods, with emphasis on the former


The main emphasis in this course is on probability models. Discrete and continuous distributions, among others the binomial, the hypergeometric, the exponential, the Poisson and the normal distributions are treated. Joint probability distributions and correlation are also covered. Examples are given from many areas. The last part of the course deals with principles for estimating unknown quantities using maximum likelihood, with confidence intervals, and with hypothesis testing.

Learning Outcomes

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:


The student

  • Fundamental concepts in probability, such as expectation, variance and correlation.
  • Discrete and continuously distributed random variables
  • Law of large numbers and the central limit theorem
  • Joint and conditional distributions
  • Parameter estimation and confidence intervals
  • Hypothesis tests and p-values

General competence

The student

  • Has a practical understanding of the probability concept as it used broadly in society
  • Perform and interpret statistical analyses

Recommended Previous Knowledge

MAT101 or MAT111 (can be taken together with STAT110).

Compulsory Assignments and Attendance


Forms of Assessment

Written examination, 5 hours.

Due to the measures taken to avoid the spread of SARS-CoV-2, UiB is closed for teaching and assessment. As a consequence, the following changes is made to assessment spring semester 2020:

  • Written home examination instead of written examination
  • Grading scale ¿Pass/Fail¿ instead of ¿A-F¿

Grading Scale

The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.

Subject Overlap

STAT101: 5 ECTS, ECON240: 4 ECTS