470-8542/02 – Special Methods of Data Analysis (SMAD)

Gurantor departmentDepartment of Applied MathematicsCredits5
Subject guarantorprof. Ing. Radim Briš, CSc.Subject version guarantorprof. Ing. Radim Briš, CSc.
Study levelundergraduate or graduate
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesFS, FEI, HGFIntended for study typesFollow-up Master, Bachelor, Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
BRI10 prof. Ing. Radim Briš, CSc.
LIT40 Ing. Martina Litschmannová, Ph.D.
VRT0020 Mgr. Adéla Vrtková
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Combined Credit and Examination 12+0

Subject aims expressed by acquired skills and competences

This subject could be considered a multidisciplinary subject in between statistics and informatics. Its aim is to expand basic knowledge of statistical methods acquired by students within the scope of the subject 541-0181 / 01 - Statistics and / or 548-0093 / 01 - Quantitative methods in geography, especially about advanced statistical methods used in technical practice combined with special computer-based procedures. After passing the subject students should be able to effectively evaluate their own data and choose a suitable method for the creating a data model. They should be able to verify usability of the data model and they should be know how to interpret results in connection with the practical focus of the task.

Teaching methods

Lectures
Project work

Summary

Computer-based data processing requires their users to be able to analyze complex problems. This subject is a combination of lectures and computer-based practical, whereby theory is firmly placed into practice. In contrast to classical mathematical statistics, emphasis is placed not on particular methods but on their appropriate combinations, enabling the assessment of data quality, the selection of a suitable statistical model, its verification and the interpretation of the results with respect to the goal of data analysis. The learning is centered around focusing more on conceptual understanding of key concepts, and statistical thinking, and less on formulas and calculations, which can now be left to PCs. Statistical skills enable students to intelligently collect, analyze and interpret data relevant to their decision-making.

Compulsory literature:

Briš R., Probability and Statistics for Engineers, 2011, electronics script, Project CZ.1.07/2.2.00/15.0132. Dostupné z http://homel.vsb.cz/~bri10/Teaching/Prob%20&%20Stat.pdf Dummer R.M.; Introduction to Statistical Science, script of VŠB-TUO FEI, 1998, ISBN 80-7078-497-0

Recommended literature:

Briš R., Probability and Statistics for Engineers, 2011, electronics script, Project CZ.1.07/2.2.00/15.0132. Dostupné z http://homel.vsb.cz/~bri10/Teaching/Prob%20&%20Stat.pdf James.L.Johnson; Probability and Statistics for Computer Science, Wiley 2003, ISBN 0-471-32672-0

Way of continuous check of knowledge in the course of semester

3 tests during the semester per 11 marks (required minimum 3 marks) 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 17 marks. The course ends with an examination, in which you can get a maximum of 67 marks. It is not possible to take an examination if student don’t have a credit. Total evaluation of the course is the sum of credit marks and exam marks. Students will pass exam if they meet the compensatory gain at least 51 marks.

E-learning

Další požadavky na studenta

No additional requirements are imposed on the student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Introduction to probability theory Random Variable Random Vector Probability models for discrete random variable Probability models for continous random variable Statistical survey and exploratory analysis Sample characteristics, Introduction to estimation theory Hypothesis testing – principle One-sample and two-samples parametric tests of hypothesis Goodness of Fit tests Tests for comparing more than two variances, ANOVA (one factor, two factors), Kruskal-Wallis test Analysis of Independence Introduction to Regression Analysis

Conditions for subject completion

Full-time form (validity from: 2015/2016 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 33  15
        Examination Examination 67  18
Mandatory attendence parzicipation:

Show history
Combined form (validity from: 2015/2016 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 33  15
        Examination Examination 67  18
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Compulsory study plan
2018/2019 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Compulsory study plan
2017/2018 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Compulsory study plan
2016/2017 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Compulsory study plan
2015/2016 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
V - ECTS - mgr. 2020/2021 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2019/2020 Full-time English Optional 401 - Study Office stu. block
IPSA Paris 2019/2020 Full-time English Choice-compulsory 301 - Study and International Office stu. block
V - ECTS - mgr. 2018/2019 Full-time English Optional 401 - Study Office stu. block
IPSA Paris 2018/2019 Full-time English Choice-compulsory 301 - Study and International Office stu. block
IPSA Paris 2017/2018 Full-time English Choice-compulsory 301 - Study and International Office stu. block
V - ECTS - mgr. 2017/2018 Full-time English Optional 401 - Study Office stu. block
V - ECTS - mgr. 2016/2017 Full-time English Optional 401 - Study Office stu. block
IPSA Paris 2016/2017 Full-time English Choice-compulsory 301 - Study and International Office stu. block
V - ECTS - mgr. 2015/2016 Full-time English Optional 401 - Study Office stu. block
IPSA Paris 2015/2016 Full-time English Choice-compulsory 301 - Study and International Office stu. block