Course: Data Analysis and Visualisation

» List of faculties » PRF » KI
Course title Data Analysis and Visualisation
Course code KI/AVD
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 4
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Babichev Sergii, prof. DSc.
  • Škvor Jiří, RNDr. Ph.D.
  • Posel Zbyšek, doc. RNDr. Ph.D.
Course content
1. Introduction to measurement theory: estimation of measurement error, error propagation and uncertainties 2. Basic concepts of descriptive statistics: methods of data processing, frequency distribution (histogram, polygon) 3. The statistical analysis of univariate data: moment/ quantile measures of central tendency, variability, skewness and kurtosis 4. Statistical analysis of multivariate data: correlation, factor and cluster analysis 5. Regression analysis: linear and nonlinear regression models 6. Analysis of time series: graphical analysis, decomposition, autocorrelation, trend modeling 7. Index analysis: simple and composite individual indices, aggregate indexes 8. Signal and image processing: filtering, transformation (Fourier, wavelets) 9. Summary of selected techniques of static and dynamic visualization

Learning activities and teaching methods
unspecified
Learning outcomes
The course focuses on the presentation of information that are necessary to the basic and comprehensive evaluation of the data. Emphasis is placed on gaining the ability to visualize data by appropriate means. An integral part of the course is the practical application of theoretical knowledge on available data using appropriate software tools (typically R, Matlab, Excel).

Prerequisites
unspecified
KI/MSW

Assessment methods and criteria
unspecified
a) two homework assignments (corresponding instructions will be announced in class sufficiently in advance) - 1. topic: data processing and statistical analysis (includes reproducible report and interactive visualization) - 2. topic: signal and image processing b) practical test (topics: regression analysis, component analysis and cluster analysis), where two tasks assigned and dealt with during last two lessons have to be passed c) written test (topics: measurement theory, index analysis)
Recommended literature
  • Hlavač V., Sedláček M. Zpracování signálů a obrazů. Praha: ČVUT, 2007. ISBN 978-80-01-03110-0.
  • Kozák J. Úvod do analýzy ekonomických časových řad. Praha: VŠE, 1994. ISBN 80-707-9760-6.
  • Popelka J., Synek V. Úvod do statistické analýzy dat. Ústí nad Labem, 2009. ISBN 978-80-7414-117-1.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Information Systems (A14) Category: Informatics courses 2 Recommended year of study:2, Recommended semester: Summer