OS3VIS - Probability and Statistics

Course specification
Course title Probability and Statistics
Acronym OS3VIS
Study programme Electrical Engineering and Computing
Module Signals and Systems
Type of study bachelor academic studies
Lecturer (for classes)
    Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
    ESPB 3.0 Status elective
    Condition Prerequisite: Mathematics 1(OO1MM1), Mathematics 2 (OO1MM2) Exclusions: Probability and statistics (OS2VIS)
    The goal Introducing students to basic methods of probability theory in discrete and continuous models: combinatory problems, conditional probability, random variables and their numerical characteristics, Laws of Large Numbers and Central Limit Theorem, and basic ideas in mathematical statistics.
    The outcome Understanding applications of methods of Probability and Statistics in solving problems from real world. Enabling students to solve simple real world problems, applying the methods of Probability and Statistics, determining the correct mathematical model and performing related parameter estimation and testing hypotheses.
    Contents of lectures Fundamental concepts and applications of combinatorics. Conditional probability and independence of events. Random variables and their distributions. Numerical characteristics of random variables. Laws of Large Numbers and Central Limit Theorem. Estimate of parameters and testing hypothesis. Least square method and Linear regression.
    Contents of exercises Through examples, tasks and problems student learns how to apply theorems and basic concepts that are learnt through theoretical contents. Especially students are prepared how to solve problems that are occurring in vocational electrotechnical subjects.
    1. Milan Merkle: Probability and statistics for engineers and engineering students, Akademska Misao, Belgrade 2010.
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    1 1 0.5
    Methods of teaching Combination of traditional presentation on blackboard, slides, communication with students through internet and individual work with students while working on home work tasks, that are scored through testing, and explanation of current topics.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures 0 Test paper 70
    Practical lessons 0 Oral examination 0
    Projects 0
    Colloquia 30
    Seminars 0