# 470-4405/03 – Probability and Statistics (PS)

 Gurantor department Department of Applied Mathematics Credits 4 Subject guarantor Ing. Martina Litschmannová, Ph.D. Subject version guarantor Ing. Martina Litschmannová, Ph.D. Study level undergraduate or graduate Study language Czech Year of introduction 2016/2017 Year of cancellation Intended for the faculties USP Intended for study types Follow-up Master
Instruction secured by
KRA0220 Ing. Jan Kracík, Ph.D.
LIT40 Ing. Martina Litschmannová, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 3+3
Combined Credit and Examination 10+10

### Subject aims expressed by acquired skills and competences

The course is designed for graduates to gain an initial idea of ​​the basic concepts and tasks that fall within the field of probability and statistics and were able to apply their knowledge in practice.

Lectures
Tutorials

### Summary

This is an introductory course in statistics. The course will emphasize methods of applied statistics and data analysis. Theoretical considerations will be included to the extent that knowledge of theory is necessary for a sound understanding of methods and contributes to the development of data analysis skills and the ability to interpret results of statistical analysis. The objective of the course is to develop sufficient knowledge of statistical tools and procedures, understanding of the underlying theory on which the procedures are based, and facility in the application of statistical tools to enable the student to incorporate sound statistical methodology into other areas of his or her own work.

### Compulsory literature:

[1] Briš, R. (2011), Probability and Statistics for Engineers, VŠB-TU Ostrava, WEB: http://homel.vsb.cz/~bri10/Teaching/Bris%20Prob%20&%20Stat.pdf [2] Dummer, R.M. (1998), Introduction to Statistical Science, VŠB-TU Ostrava, ISBN 80-7078-497-0

### Recommended literature:

[1] StatSoft, Inc. (2013). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: http://www.statsoft.com [2] HILL, T. & LEWICKI, P. (2007). STATISTICS: Methods and Applications. StatSoft, Tulsa, OK.

### Way of continuous check of knowledge in the course of semester

Presence form: Discussions: - 10 short tests during the semester per 2 points, 20 points overall (minimum required: 6 points) - 4 homeworks per 5 points, 20 points overall (minimum required: 5 points for each task) Exam: - 10 short tests during the semester per 2 points, 20 points overall (minimum required: 6 points) Combined form: Discussions: - 3 homeworks during the semester per 10 points, for a total maximum of 30 points (minimum required: 3 points for each homework) - Test with a maximum of 10 points (minimum required: 1 point) - Semester project, max 20 points (minimum required: 10 points) Exam: - written exam (practical part: max. 50 points, required minimum: 25 points, theoretical part: max. 10 points, required minimum: 2 points) For successful completion of the Discussions is given credit. Students will receive credit if they meet the required minimum of each of the sub-tasks and compensatory gain at least 20 points. Students will pass the exam if they meet the the required minimum of each of the sub-tasks and compensatory gain (Discussions and Exam) at least 51 points.

### E-learning

Presence form: Active participation in at least 80% of discussions.

### Prerequisities

Subject has no prerequisities.

### Co-requisities

Subject has no co-requisities.

### Subject syllabus:

1) Introduction to Probability Theory 2) Discrete random variable 3) Selected distributions of discrete random variables 4) Continuous random variable 5) Selected distributions of continuous random variables 6) Limit Theorems 7) Random Vector 8) Introduction to statistics, exploratory analysis 9) The survey, random sampling and basic sample characteristics 10) Introduction to estimation theory 11) Introduction to hypothesis testing (principle) 12) Hypotheses testing - mean, probability, variance (one-sample and two-sample tests) 13) Analysis of variance (verification normality, ANOVA and Kruskal-Wallis test)

### Conditions for subject completion

Full-time form (validity from: 2016/2017 Winter semester)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
Credit Credit 40 (40) 20
Průběžné testy Written test 20  6
Domácí úkoly Other task type 20  10
Examination Examination 60 (60) 27
Praktická část Written examination 50  25
Teoretická část Written examination 10  2
Mandatory attendence parzicipation: Participation at all exercises is obligatory, 2 apologies are accepted. Participation at lectures is recommended, knowledge of lecture materials is a prerequisite for participation at the exercises.

Show history
Combined form (validity from: 2016/2017 Winter semester)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
Credit Credit 40 (40) 20
Domácí úkol 1 Other task type 10  3
Domácí úkol 2 Other task type 10  3
Domácí úkol 3 Other task type 10  3
Zápočtový test Written test 10  1
Examination Examination 60 (60) 27
Praktická část Written examination 50  25
Teoretická část Written examination 10  2
Mandatory attendence parzicipation:

Show history

### Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2018/2019 (N2658) Computational Sciences (2612T078) Computational Sciences P Czech Ostrava 1 Choice-compulsory study plan
2017/2018 (N2658) Computational Sciences (2612T078) Computational Sciences P Czech Ostrava 1 Choice-compulsory study plan
2016/2017 (N2658) Computational Sciences (2612T078) Computational Sciences P Czech Ostrava 1 Choice-compulsory study plan

### Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner