Course syllabus AST - Aplikovaná statistika (FBE - SS 2019/2020)


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Course code: AST
Course title in language of instruction: Aplikovaná statistika
Course title in Czech: Aplikovaná statistika
Course title in English: -- item not defined --
Mode of completion and number of credits: Exam (5 credits)
(1 ECTS credit = 28 hours of workload)
Mode of delivery/Timetabled classes: full-time, 2/2 (hours of lectures per week / hours of seminars per week)
Language of instruction: Czech
Level of course: bachelor
Semester: SS 2019/2020
Name of lecturer: Mgr. Veronika Blašková, Ph.D. (examiner, instructor, lecturer)
doc. Ing. Luboš Střelec, Ph.D. (examiner, instructor, lecturer, supervisor)
Prerequisites: Statistics
 
Aims of the course:
The course objective is acquirement of advanced statistical and econometric methods knowledge. Competence to apply statistical tools and built-in functions of software Statistica and Gretl. Knowledge and skills learned by students in this course are expected to be used during work on student bachelor's thesis.
 
Course contents:
1.Numeric and graphical characteristics (allowance 2/2)
 
a.Absolute and relative frequency
b.Frequency distribution
c.Statistical characteristics
d.Numeric characteristics
e.Graphical presentation

2.Parametric tests (allowance 4/4)
 
a.One-sample and two-samples tests about parameters of Normal distribution
b.One-sample and two-samples tests about parameters of Bernoulli distribution
c.Correlation analysis
d.One-way and two-way analysis of variance
e.Post-hoc methods of multiple comparison
f.Application of parametric methods in economic data

3.Nonparametric tests (allowance 4/4)
 
a.Sign test
b.Wilcoxon signed-rank test
c.Mann-Whitney-Wilcoxon test
d.Two-sample Kolmogorov-Smirnov test
e.Kruskal-Wallis test
f.Post-hoc methods of multiple comparison for nonparametric ANOVA

4.Fundamentals of nominal and ordinal data analysis (allowance 4/4)
 
a.Contingency table
b.Testing hypothesis about independency in qualitative data
c.Measures of dependency for nominal or ordinal variables
d.Evaluation of questionnaire

5.Statistical comparison (allowance 4/4)
 
a.Absolute and relative changes
b.Individual, composite and aggregate indices
c.Indices decomposition
d.Price indices

6.Specific regression problems (allowance 3/3)
 
a.Parameter stability
b.Missing data
c.Outliers
d.Robust regression

7.Advanced data analysis methods (allowance 4/4)
 
a.Difference in differences method
b.Quantile regression
c.Spectral analysis

8.Modeling of selected economic patterns (allowance 3/3)
 
a.Practical examples of econometric modeling

 
Learning outcomes and competences:
-- item not defined --
Type of course unit: required
Year of study: Not applicable - the subject could be chosen at anytime during the course of the programme.
Work placement: There is no compulsory work placement in the course unit.
Recommended study modules: -
 
Learning activities and study load (hours of study load):
Type of teaching methodDaily attendance
Direct teaching
     lecture28 h
     practice28 h
     consultation4 h
Self-study
     preparation for exam20 h
     elaboration and execution of projects60 h
Total140 h
 
Assessment methods:
During semester, student performance is evaluated upon submission of written project (minimum 50% is required). The course is completed by a written examination covering the theoretical and practical part (minimum 50% is required).
 
Recommended reading:
TypeAuthorTitlePublished inPublisherYearISBN
RQBUDÍKOVÁ, M. -- KRÁLOVÁ, M. -- MAROŠ, B.Průvodce základními statistickými metodamiPrahaGrada2010978-80-247-3243-5
RQCIPRA, T.Finanční ekonometriePrahaEkopress2008978-80-86929-43-9
REGREENE, W H.Econometric analysisBoston [u.a.]Pearson2012978-0-273-75356-8
REEconometricsBerlinSpringer978-3-642-20058-8
RENEUBAUER, J. -- SEDLAČÍK, M. -- KŘÍŽ, O.Základy statistiky: aplikace v technických a ekonomických oborechPrahaGrada2012978-80-247-4273-1

RQrequired
RErecommended


Last modification made by Ing. Jiří Gruber on 12/04/2019.

Type of output: