Topic outline

  • Contact information

    For general information about the course, please send your enquiry to, which will reach the lecturer of the course.

    Course description

    The course introduces the fundamental concepts of probability theory and statistics. At the successful completion of the course, you can compute probabilities of composite events, can apply relevant discrete and continuous probability distributions to model corresponding phenomena, can differentiate between dependent and independent stochastic random variables and can compute statistics of random vectors. You know methods for estimating the parameters of a statistical model, understand the basics of Bayesian inference, can formulate statistical hypotheses and perform statistical tests, can interpret the resulting p-value correctly. By attending the lectures and doing the weekly in-class exercise problems and homework assignments, you get the opportunity to learn, apply and reinforce each of the introduced concepts.  


    Basic calculus (derivative and integral).

    On-campus teaching

    All lectures and group exercise sessions take place In Otaniemi. 

    Course content

    • Probability: concept and basic rules
    • Random variables and probability distributions
    • Expected value and the law of large numbers
    • Variance and correlation, stochastic dependence
    • Normal approximation
    • Statistical datasets, summary statistics and histograms
    • Parameter estimation and stochastic models
    • Confidence intervals
    • Bayesian inference
    • Testing of simple statistical hypothesis