Course syllabus DMSA - Quantitative Methods (FBE - 2017/2018 - post-graduate studies)


     ECTS syllabus          Syllabus          Timetable          


     English          


Course code: DMSA
Course title in language of instruction: -- item not defined --
Course title in Czech: Quantitative Methods
Course title in English: Quantitative Methods
Mode of completion and number of credits: Exam (0 credits)
(1 ECTS credit = 28 hours of workload)
Mode of delivery/Timetabled classes: full-time, 0/0 (hours of lectures per week / hours of seminars per week)
part-time, 0/0 (lectures per period / seminars per period)
Language of instruction: Czech, English
Level of course: -- item not defined --
Semester: 2017/2018
Name of lecturer: doc. Mgr. David Hampel, Ph.D. (examiner)
doc. Ing. Mgr. Jitka Janová, Ph.D. (supervisor)
doc. Ing. Luboš Střelec, Ph.D. (examiner)
Prerequisites: none
 
Aims of the course:
Objective of the subject is to develop students' knowledge in the field of applying quantitative methods in economic research.
 
Course contents:
1.Regression models (allowance 0/0)
 
a.Multiple linear and non-linear regression and correlation
b.Methods of construction and premises of linear regression models
c.Estimations in multiple linear regression and correlation
d.Testing hypotheses in multiple linear regression and correlation
e.Multiple regression and correlation analysis using computers

2.Time series models (allowance 0/0)
 
a.Index analysis
b.Fisher axiomatic theory of indices
c.Summary indices of the 3rd generation
d.Modern methods of index decomposition and absolute differences
e.Quantitative part of pyramidal analysis

3.Multi-dimensional statistical methods (allowance 0/0)
 
a.Classification of multi-dimensional statistical methods
b.Methods of correlation structures analysis (analysis of main components, factor analysis, canonical correlation analysis)
c.Methods of multi-dimensional classification and typology (discrimination analysis, cluster analysis)
d.Solution of multi-dimensional analysis issues using computers

4.Linear programming (allowance 0/0)
 
a.Multi-programming
b.Targeted programming
c.Parametric programming
d.Specific types of distribution problems

5.Non-linear programming (allowance 0/0)
 
a.Dynamic programming
b.Discrete problems of dynamic programming
c.Bellman principle of optimum
d.One- and two-parameter reproduction model
e.Conjunctive optimisation problems
f.Pontrjagin principle of maximum

6.Structural analysis (allowance 0/0)
 
a.Structural optimisation models
b.Stability of technical coefficients and their updating
c.Dynamic structural models
d.Sgtochastic models

7.Markov chains (allowance 0/0)
 
a.Markov processes, queuing systems
b.Inventory management models
c.Models of renovation
d.Simulation models

 
Learning outcomes and competences:
-- item not defined --
Type of course unit: optional
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 attendanceCombined form
Total0 h0 h
 
Assessment methods:
Oral examination within the Examination board 2.
 
Recommended reading:
TypeAuthorTitlePublished inPublisherYearISBN
RQACZEL, A D. -- SOUNDERPANDIAN, J.Complete business statisticsBostonMcGraw-Hill2006007-124416-6
RQFREEDMAN, D.StatisticsNew YorkW.W. Norton & Co.978-0-393-92972-0
RQFAHRMEIR, L. -- TUTZ, G.Multivariate statistical modelling based on generalised linear modelsNew YorkSpringer Verlag20010-387-95187-3
RQHINDLS, R. et al.Statistika pro ekonomyPrahaProfessional Publishing2007978-80-86946-43-6
RQLAY, D C.Linear algebra and its applicationsBostonAddison Wesley20030-201-70970-8

RQrequired
RErecommended


Last modification made by Ing. Jiří Gruber on 08/08/2017.

Type of output: