Course content

The course provides an introduction to probability calculations and includes the following topics; the probability axioms, probability laws, conditional probability, independence, combinatorics, the urn model, random variables, mean value, variance, standard deviation, discrete and continuous univariate probability distributions, transformation of random variables, discrete and continuous bivariate distributions, covariance and correlation, independent random variables, computing the mean by conditioning, moment generating functions, cumulant generating functions, order statistics,
binomial distribution, hyper-geometric distribution, geometric distribution, Poisson distribution, exponential distribution, normal distribution, the central limit theorem, chi-squared distribution, Students t-distribution, Fishers F-distribution, multinomial distribution and binormal distribution.

Learning outcome

This course give the students basic knowledge in probability theory. It will be focused on stochastic modelling by relating the theory to practical problems. Practical understanding of the models leading to the most well known probability distributions will be emphasized. The course also give the students the theoretical background required to take the next course ST1201 Statistical Methods.

Learning methods and activities

Lectures and compulsory exercises. Written final examination is the basis for the grade awarded in the course.

Compulsory assignments

• Exercises

Recommended previous knowledge

The course is based on MA1101 Basic calculus I

Course materials

Will be announced at the start of the course.

Credit reductions