Undergraduate study programme

Ak.g.2014./2015.2015./2016.2016./2017.2017./2018.

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Probability and Statistics P402

ECTS 5 | P 30 | A 30 | L 0 | K 0 | ISVU 74047

Course groups

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Course lecturers

RUDEC TOMISLAV, Lecturer
HARTMANN-TOLIĆ IVANA, Associate
GALIĆ RADOSLAV, Lecturer

Course description

Fundamentals of combinatorics. Algebra of events. Probability and properties. Random variable. Distribution function of a random variable. Discrete and continuous probability distributions (hypergeometric, binominal, Poisson, normal, uniform, exponential, Chi-squared, student`s t-distribution). Numerical properties of distributions. Two-dimensional probability distributions. Moments and correlations. Statistical set with parameters. Empirical and two-dimensional distributions. Correlation and regression analysis. Samples and numerical properties of samples. Parameter estimation. Interval estimation. Statistical hypothesis testing. Examples of statistical models, statistical thinking and application of statistical programmes. Writing a seminar paper.

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. To prepare students for lifelong learning process and for the use of mathematical tools in application.

Teaching methods

Students are obliged to attend both lectures and exercises.

Student assessment

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

Obligatory literature

1. "Galić, R. Vjerojatnost i statistika. Osijek: ETF, 2013. "

2. "Montgomery, D.C. Applied Statistics and Probability for engineers. USA: Wiley, 2014. "

3. R. Galić, Statistika, ETFOS, Osijek, 2004

4. R. Galić, Vjerojatnost i statistika, ETFOS, Osijek, 2013.

Pretraži literaturu

Recommended additional literature

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

2. Ž. Pauše, Uvod u matematičku statistiku, Školska knjiga, Zagreb, 1995.

3. Ž. Pauše, Vjerojatnost i stohastički procesi, Školska knjiga, Zagreb, 2004

4. G. M. Clarke, D. Cooke, A Basic Course in Statistics, Arnold, London, 1992.

5. R. Galić, Vjerojatnost , ETFOS, Osijek, 2004

ECTS credits

An ECTS credit value has been added according to calculation of time required for studying and successful course completion.

Examination methods

The final examination consists of the written and the oral part. Students can take the final examination after the completion of lectures and exercises.

Course assessment

Conducting an anonymous questionnaire filled in by students after course completion, an analysis of students' final assessments and their overall success.

Overview of course assesment

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

1. definirati, objasniti, praktično primijeniti osnovna pravila prebrojavanja i osnovne pojmove iz kombinatorike;

2. definirati, pravilno tumačiti osnovne pojmove iz teorije vjerojatnosti te iskazati i praktično primijeniti pravila za izračunavanje vjerojatnosti unije i presjeka događaja, uvjetne vjerojatnosti, formulu potpune vjerojatnosti i Bayesovu formulu;

3. definirati, pravilno tumačiti i razlikovati pojmove slučajne varijable (diskretne/kontinuirane, jednodimenzionalne/dvodimenzionalne), matematičkog očekivanja, standardne devijacije i pravilno ih koristiti pri rješavanju praktičnih primjera; odrediti i pravilno interpretirati funkcije regresije za dvodimenzionalne slučajne varijable;

4. definirati osnovne pojmove statistike te za praktični primjer odabrati i primijeniti odgovarajuće statističke metode i postupke, analizirati, prikazati i ispitati reprezentativnost rezultata, te odrediti točkaste i intervalne procjene očekivanja i varijance

5. definirati i razlikovati osnovne pojmove statističkih testova i primijeniti odgovarajuće statističke testove na praktičnim primjerima



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Student's activity Workload ECTS (Workload/30) Learning outcomes
Upon successful completion of the course, students will be able to:
Teaching
method
Assessment method Points
Attendance
Lectures, Auditory exercises

ECTS
Lectures, Auditory exercises Attendance register. Mandatory attendance percentage is:
%

This percentage defines the minimum workload for the activity. The maximum is defined by the study programme.
Min

Max

Oral exam Workload
ECTS

Oral exam Assessment of student's answers Min

Max

Σ Activities Σ Workload
0
Σ ECTS
0
Σ Max
0