Course syllabus PSM - Advanced Statistical Methods and Models (FBE - SS 2015/2016)


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Course code:
PSM
Course title in Czech:
Advanced Statistical Methods and Models
Course title in English: Advanced Statistical Methods and Models
Semester:
SS 2015/2016
Mode of completion and number of credits: Exam (6 credits)
Mode of delivery and timetabled classes:
full-time, 2/2 (hours of lectures per week / hours of seminars per week)
Level of course:
master continuing
Course type:
required
Type of delivery:
usual, consulting
Mode of delivery for our mobility students abroad:
-- item not defined --
Language of instruction: Czech
Course supervisor:
doc. Mgr. David Hampel, Ph.D.
Course supervising department:
Faculty:
Teachers: doc. Mgr. David Hampel, Ph.D. (examiner, instructor, lecturer, supervisor)
Prerequisites:
 
Timetable in this semester:
-- item not defined --
 
Aim of the course and learning outcomes:
Theoretical and practical experience in the application of advanced statistical methods. Knowledge of the principles of work with modern computer system Matlab. Correct presentation of statistical outputs. The use of multivariate statistical methods for economic data. Students should be able effectively perform superior analysis of macroeconomic and microeconomic data after the course.
 
Course content:
1.
Basic using of the computational system Matlab (allowance 6/6)
 
a.
Principle of the work in the computational system Matlab
b.
Algoritmization of statistical and econometrical tasks
c.
Batch processing of data

2.
Presentation of statistical outputs (allowance 2/2)
 
a.Methodology of statistical outputs presentation
b.
Common mistakes in presentation of numerical and graphical outputs
c.
"Big Data" concept

3.
Selected statistical methods, tests and procedures (allowance 4/4)
 
a.Pearson's and Spearman's concept of correlation
b.Testing dependency of ordinal characteristics
c.
Odds ratio
d.General linear hypothesis
e.
Testing equality of at least three mean values (factor ANOVA)

4.
Problems of classification (allowance 2/2)
 
a.
Hierarchical cluster analysis
b.
Dendrogram
c.
Further classification techniques

5.
Principal component analysis (allowance 2/2)
 
a.
Idea of the method
b.
Graphical outputs of the analysis

6.
Factor analysis (allowance 2/2)
 
a.
Idea of the method
b.Identification of factors

7.
Panel data analysis (allowance 4/4)
 
a.
Introduction to the problem
b.Practical realisation of the analysis

8.
VEC model (allowance 2/2)
 
a.Definition, relation to the VAR model
b.
Practical application

9.Nonlinear models in economics
  
a. Specifika odhadu parametrů nelineárních modelů
b. Vybrané nelineární modely
(allowance 2/2)
 
a.
Specifics of nonlinear model parameters estimation
b.
Selected nonlinear models

10.
Simulation of economic phenomena (allowance 2/2)
 
a.
Generation of random variables
b.
Simulations related to multivariate regression model
c.Creating scenarios

Learning activities and teaching methods:
Type of teaching method
Daily attendance
lecture
28 h
practice
28 h
preparation for exam
37 h
preparation for regular assessment40 h
preparation of presentation
5 h
writing of seminar paper
30 h
Total
168 h
 
Assessment methods:
For assessment, the active participation in seminars and succesful advocation of semester project are required. The course is completed by a written examination covering verification of the theoretical knowledge and oral practical examination. Part of the final evaluation of the course is to advocate semester project. The same requirements hold for combined form of study except active participation in seminars.
 
Assessment criteria ratio:
Requirement typeDaily attendance
Total
0 %
 
Recomended reading and other learning resources:
Basic:
Mastering MATLAB. 1st ed. Harlow: Pearson, 859 p. International edition. ISBN 978-0-273-75213-4.
HEBÁK, P. et al. Statistické myšlení a nástroje analýzy dat. 1st ed. Praha: Informatorum, 2013. 877 p. ISBN 978-80-7333-105-4.
MELOUN, M. -- MILITKÝ, J. -- HILL, M. Statistická analýza vícerozměrných dat v příkladech. 2nd ed. Praha: Academia, 2012. 750 p. Gerstner ;. ISBN 978-80-200-2071-0.

Recommended:
ANDĚL, J. Statistické metody. 4th ed. Praha: Matfyzpress, 2007. 299 p. ISBN 978-80-7378-003-6.
Statistical rules of thumb. 2nd ed. Hoboken: Wiley, 272 p. Wiley series in probability and statistics. ISBN 978-0-470-14448-0.
HEBÁK, P. et al. Vícerozměrné statistické metody [3]. 1st ed. Praha: Informatorium, 2005. 255 p. ISBN 80-7333-039-3.
LÜTKEPOHL, H. New introduction to multiple time series analysis. Berlin: New York :, 2005. 764 p. ISBN 3-540-40172-5.
TUČEK, D. Modelování, simulace a optimalizace podnikových procesů v praxi . 1st ed. Zlín: ČSOP, 2011. ISBN 978-80-260-0023-5.
ZAPLATÍLEK, K. -- DOŇAR, B. MATLAB pro začátečníky. 2nd ed. Praha: BEN - technická literatura, 2005. 151 p. ISBN 80-7300-175-6.

Course listed in study plans for this semester:
Track SNST Economic Statistics, full-time form, initial period WS 2015/2016
Track SNST Economic Statistics, full-time form, initial period SS 2015/2016
 
Course listed in previous semesters: SS 2019/2020, SS 2018/2019, SS 2017/2018, SS 2016/2017, SS 2014/2015 (and older)
Teaching place: -- item not defined --


Last modification made by Ing. Jiří Gruber on 11/30/2015.

Type of output: