- Class 30
- Practice 30
- Independent work 90
Probability and statistics
Lecturers and associates
- Full Professor PhD Mario Krnić
- Iva Golubić, Senior Lecturer
- Hrvoje Kovač, Lecturer
- Zoran Lovrić, Instructor
- Ivan Nađ, Lecturer
The objective of this module is to enable students to learn:
• the concepts in probability in statistics
• to apply methods of analysing data
• make results-based decisions.
Students learn the:
theoretical and practical foundations of probability and statistics,
the related areas of mathematics to calculate and analyze relative frequency of events, measures of central tendencies and measures of dispersions.
Students undertake this module in the third semester after having completed and acquired the mathematical skills, from previous modules, to successfully complete this module.
It is important for students to take this module because probability and statistics are essential in the modern world, which is full of statistical information and interpretation. The knowledge students acquire in this module can be used in solving engineering problems and thus contributes to the overall skillset for their future employment as software and system engineers. This module will expose students to a particular experience when dealing with statistical problems and probability issues in a practical way, both individually and in teams.
1. Krnić, M. (2020) Probability and Statistics Handbook. Zagreb: Algebra.
1. Dekking, F.M., Kraaikamp, C., Lopuhaä, H.P., Meester, L.E. (2005) A Modern Introduction to Probability and Statistics: Understanding Why and How.1st edn. [s.l.] Springer
1. Illowsky, B., Dean, S. (2018) Introductory Statistics. [s.l.] Openstax.
2. Witte, R. S., Witte, J. S. (2017) Statistics.11th edn. [s.l.] Wiley.
Minimal learning outcomes
- Adopt the basic combinatorial notions and rules and calculate the probability in the classical probability space.
- Determine the conditional probability of an event.
- Determine basic numerical characteristics of a given discrete random variable and evaluate numerical characteristics of some continuous random variables, especially the normal and exponential random variables.
- Calculate the basic quantities for given discrete statistical data.
Preferred learning outcomes
- Recognize the corresponding structures in enumerative combinatorics and calculate the probability in some infinite probability spaces.
- Apply conditional probability when using total probability rule and the Bayes rule.
- Determine the law of distribution of a random variable in the corresponding problem and apply important properties of binomial, Poisson, normal and exponential random variables in solving complex problems.
- Calculate some quantities for given continuous statistical data.