Course objectives:
|
To acquaint students with procedures for statistical processing multivariate of economic data using appropriate statistical software.
|
Requirements on student
|
Credit:
Complete credit tests in the sum of min. 60% inclusive.
Exam:
Exam is combined, consists of practical part and theoretical part.
|
Content
|
- Data acquisition methods
- Data matrix
- Examining data quality
- Multivariate data analysis
- Principal component analysis
- Factor analysis
- Multiple regression
- Logistic regression
- Discriminant analysis
- Classification trees
- Economic time series
|
Activities
|
|
Fields of study
|
e-learning (Moodle)
|
Guarantors and lecturers
|
-
Guarantors:
Doc. RNDr. Mikuláš Gangur, Ph.D. (100%),
-
Lecturer:
Doc. RNDr. Mikuláš Gangur, Ph.D. (100%),
Ing. Mgr. Milan Svoboda, Ph.D. (100%),
-
Tutorial lecturer:
Doc. RNDr. Mikuláš Gangur, Ph.D. (100%),
Ing. Mgr. Milan Svoboda, Ph.D. (100%),
|
Literature
|
-
Basic:
E-kurz Vícerozměrná analýza ekonomických dat
(Mikuláš Gangur)
-
Basic:
Hebák, Petr. (2015). Statistické myšlení a nástroje analýzy dat. Praha : Informatorium, Vyd. 2.
-
Basic:
Hindls, Richard. (2018). Statistika pro ekonomy. Professional Publishing, Vyd. 1.
-
Extending:
HAIR, F. Joseph, BLACK, C. William, BABIN, J. Barry, ANDERSON E. Rolph. (2009). Multivariate Data Analysis. 7th edition. Prentice Hall.
-
Recommended:
Arlt, Josef; Arltová, Markéta. (2009). Ekonomické časové řady. Praha : Professional Publishing.
-
On-line library catalogues
|
Time requirements
|
All forms of study
|
Activities
|
Time requirements for activity [h]
|
Preparation for comprehensive test (10-40)
|
46
|
Contact hours
|
52
|
Preparation for an examination (30-60)
|
58
|
Total
|
156
|
|
Prerequisites
|
Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
Choose the appropriate statistical method for a given task at the level of subjects (KEM/STA and KEM/STZD) |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
To solve the statistical task at the level of subjects (KEM/STA and KEM/STZD) |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
|
Learning outcomes
|
Knowledge - knowledge resulting from the course: |
explain selected methods of multivariate statistical analysis of economic data |
explain the essence of multivariate data analysis methods |
Skills - skills resulting from the course: |
Choose a suitable data analysis method |
Analyze data using statistical SW |
Competences - competences resulting from the course: |
N/A |
|
Assessment methods
|
Knowledge - knowledge achieved by taking this course are verified by the following means: |
Practical exam |
Skills demonstration during practicum |
Test |
Skills - skills achieved by taking this course are verified by the following means: |
Practical exam |
Skills demonstration during practicum |
Test |
Competences - competence achieved by taking this course are verified by the following means: |
Practical exam |
Skills demonstration during practicum |
Test |
|
Teaching methods
|
Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Interactive lecture |
Self-study of literature |
Skills - the following training methods are used to achieve the required skills: |
Practicum |
Individual study |
Competences - the following training methods are used to achieve the required competences: |
Lecture |
Interactive lecture |
Practicum |
Individual study |
|