Probability with Applications

The course provides a general introduction to probability calculation, with applications from science and medicine, and includes the following topics; events and sample space, the probability axioms, probability laws, conditional probability, independence, combinatorics, the urn model, random variables, mean, variance, standard deviation, discrete and continuous probability distributions, bivariate distributions, covariance and correlation, independent random variables, computing the mean by conditioning, binomial distribution, hyper-geometric distribution, geometric distribution, Poisson distribution, exponential distribution, normal distribution, the central limit theorem, multinomial distribution and binormal distribution, Poisson distribution and survival distributions.

This course will give the students basic knowledge in probablity 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 shall also give the students the
theoretical background required to take the next course ST0201 Statistics with Applications.

Lectures and compulsory exercises. Written examination. Retake of examination may be given as an oral examination.