## Professional study programme

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## Course groups

Prikaži sve grupe na predmetu

## Course description

Algebra of events. Probability of events. Basic probability properties. Classic definition of probability. Conditional probability and independence. Discrete probabilistic space. Discrete random variable. Binominal and Poisson distribution. Continuous random variable. Normal distribution. Normal distribution parameters. t distribution. Empirical one-dimensional and two-dimensional distribution. Sample and parameter samples. Basic statistical methods. Statistical estimation theory. Statistical decision making. Hypotheses testing. Basics of correlation theory.

## Knowledge and skills acquired

Introduction to statistical terminology and laws, construction of statistical models and their application in engineering, process control, quality control and other problems. Preparing students for a lifelong learning process and the applicational use of mathematical tools.

## Teaching methods

Lectures and solving statistical problems.

## Student requirements

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

## Monitoring of students

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

## Student assessment

During the semester students can take several tests which replace the written examination. This ensures a continuous assessment of studentsâ€™ work and knowledge.

## Obligatory literature

1. 1 Pavlić, I. Statistička teorija i primjena Zagreb: Tehnička knjiga, 2000

2. 2 R. Galić Vjerojatnost i statistika Osijek: ETF, 2013;

3. 3 V. Bahovec, K.Dumičić et al. Statistika Zagreb: Element, 2014

4. 4 R. Galić Statistika ETF, Osijek, 2004

Pretraži literaturu na:

1. 1 Ž.Pauše Uvod u matematičku statistiku Školska knjiga,Zagreb,1993

2. 2 Ž.Pauše Vjerojatnost, informacija, stohastički procesi Školska knjiga, Zagreb, 1988

## Examination methods

Seminar paper and oral exam.

## Course assessment

Conducting university questionnaires on teachers (student-teacher relationship, transparency of assessment criteria, motivation for teaching, teaching clarity, etc.). Conducting Faculty surveys on courses (upon passing the exam, student self-assessment of the adopted learning outcomes and student workload in relation to the number of ECTS credits allocated to activities and courses as a whole).

## Overview of course assesment

Learning outcomes
Upon successful completion of the course, students will be able to:

1. define the concepts of permutation, combinations and variations, and know how to analyse, compare and define which terms refer to a particular task

2. define the concepts of a probability of occurrence and conditional probability, and define the adopted properties of these terms to interpret the task solution

3. distinguish the discrete and continuous distribution, be able to explain binomial, poisson, hypergeometric, normal, uniform, exponential distribution as well as solve tasks from that area

4. explain the terms statistical set and frequency distribution, and create groups for the given statistics tasks

5. calculate and interpret measures of statistical data types

6. calculate and interpret the results of tasks in the field of point and interval estimates of the parameters of the basic set

Aktivnosti studenta: Vidi tablicu aktivnosti