714-0951/03 – Mathematical statistics and data analysis (MSAD)

Gurantor departmentDepartment of Mathematics and Descriptive GeometryCredits10
Subject guarantorMgr. Marcela Rabasová, Ph.D.Subject version guarantorMgr. Marcela Rabasová, Ph.D.
Study levelpostgraduateRequirementChoice-compulsory
YearSemesterwinter + summer
Study languageCzech
Year of introduction2013/2014Year of cancellation2019/2020
Intended for the facultiesHGFIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
KUC14 prof. RNDr. Radek Kučera, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 2+0
Combined Examination 2+0

Subject aims expressed by acquired skills and competences

The aim of the course is to provide theoretical and practical foundation for understanding the importance of basic probability concepts and teach the student statistical thinking as a way of understanding the processes and events around us and to acquaint him with the basic methods of gathering and analyzing statistical data.

Teaching methods

Individual consultations
Project work

Summary

1. Descriptive statistics - statistical file with one factor, statistical file with two factors, grouped frequency distribution 2. Inductive statistics - random sample, point and interval estimations of parameters, hypothesis testing 3. Regression analysis - least squares approximation, linear regression, nonlinear regression

Compulsory literature:

Dummer R. M.: INTRODUCTION TO STATISTICAL SCIENCE. VŠB-TU Ostrava 1998; ISBN 80-7078-497-0

Recommended literature:

Radim Briš, Petra Škňouřilová. STATISTICS I. VŠB - Technical University of Ostrava, Ostrava 2007.

Way of continuous check of knowledge in the course of semester

Tests and credits ================= Teaching is based on individual consultations. Program and the exam questions are analogous to the program of lectures.

E-learning

Další požadavky na studenta

Requirements are given by the outline of the subject.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Descriptive statistics - statistical file with one factor, statistical file with two factors, grouped frequency distribution 2. Inductive statistics - random sample, point and interval estimations of parameters, hypothesis testing 3. Regression analysis - least squares approximation, linear regression, nonlinear regression

Conditions for subject completion

Combined form (validity from: 2013/2014 Winter semester, validity until: 2019/2020 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Examination Examination  
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2018/2019 (P2116) Mineral Raw Materials (2102V009) Processing P Czech Ostrava Choice-compulsory study plan
2018/2019 (P2116) Mineral Raw Materials (2102V009) Processing K Czech Ostrava Choice-compulsory study plan
2017/2018 (P2116) Mineral Raw Materials (2102V009) Processing P Czech Ostrava Choice-compulsory study plan
2017/2018 (P2116) Mineral Raw Materials (2102V009) Processing K Czech Ostrava Choice-compulsory study plan
2015/2016 (P3646) Geodesy and Cartography (3646V001) Mine Surveying and Geodesy K Czech Ostrava Choice-compulsory study plan
2014/2015 (P3646) Geodesy and Cartography (3646V001) Mine Surveying and Geodesy K Czech Ostrava Choice-compulsory study plan
2013/2014 (P3646) Geodesy and Cartography (3646V001) Mine Surveying and Geodesy K Czech Ostrava Choice-compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner