545-0090/01 – Statistical Data Processing (ZpracDat)
| Gurantor department | Department of Economics and Control Systems | Credits | 5 |
| Subject guarantor | RNDr. Radmila Sousedíková, Ph.D. | Subject version guarantor | RNDr. Radmila Sousedíková, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 2 | Semester | summer |
| | Study language | Czech |
| Year of introduction | 2015/2016 | Year of cancellation | 2020/2021 |
| Intended for the faculties | HGF | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
Generating knowledge concerning elements and methods of statistical data processing, and applying the knowledge to analysis of statistical data sets.
Teaching methods
Lectures
Individual consultations
Tutorials
Summary
Subject concerns methods for describing sets of data, confidence intervals and tests of hypotheses, regression and correlation analysis, and time series analysis.
Compulsory literature:
TRUXILLO, C. Statistical Analysis Using Enterprise Guide. Software Course Notes. SAS Institute Inc. USA, 2001.
Recommended literature:
SULLIVAN M. Fundamentals of Statistics. USA: Prentice Hall, 2005. ISBN: 0-13- 146449-3 Gunderson A. Interactive Statistics. [online]. USA, Prentice Hall, 2002. HTML format.URL:ftp://ftp.prenhall.com/pub/esm/web_marketing/mathematics_development a l.s-072/aliaga/aliaga.htm>
Additional study materials
Way of continuous check of knowledge in the course of semester
Regular feedback on the progress of knowledge during the current term is provided by semester projects and knowledge checks
E-learning
The learning management system Moodle (lms.vsb.cz) is used for communication beyond full-time teaching, through which communication is enabled not only between the teacher and students, but also between students themselves.
Other requirements
There are no additional requirements.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Collecting data
2. Frequency distribution, statistical plots
3. Basic characteristics of statistical data set
4. Point and interval estimation
5. Hypothesis testing
6. Basic methods of dependence description, analysis of variance
7. Regression analysis
8. Correlation analysis
9. Time series
10. Basic characteristics of time series
11. Time series components
12. Index numbers
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction