Course title | State Final Exam: Analysis of Economic Data and Decision Making |
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Course code | KMI/BZAER |
Organizational form of instruction | no contact |
Level of course | Bachelor |
Year of study | not specified |
Semester | Winter and summer |
Number of ECTS credits | 0 |
Language of instruction | Czech |
Status of course | Compulsory-optional |
Form of instruction | Face-to-face |
Work placements | This is not an internship |
Recommended optional programme components | None |
Lecturer(s) |
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Course content |
Examination topics: 1. BASIC PRINCIPLES, PROBABILITY AND RANDOM VARIABLES population and sample, type of variables, scale of measurement, data description and presentation, exploration data analysis, events and their probability, probability counting, Bayes conception of probability, description of distribution for discrete and continuous random variable, the most used discrete and continuous probability distributions, central limit theorem and law of large numbers, theoretical (sample) distributions. 2. MATHEMATICAL STATISTICS, HYPOTHESIS TESTING AND REGRESSION techniques and forms for random sample, properties of point estimations, construction of point and confidence intervals, interval estimator for mean, proportion and variability for normal distribution sample, hypothesis testing, basic conception, tests construction, one sample t-test, equality parameters test for two and more populations, basic non parametric tests, simple regression with one independent variable (X), assumptions, estimation of parameters, standard error of estimator, testing of hypothesis about b, quality of model, multivariable regression, multicollinearity, heteroscedasticity and autocorrelation in RA, Extreme, outlier and generally powerful observations, analysis of variance and its using in regression, different types of correlation coefficients, properties and using. 3. ANALYSIS OF TIME SERIES economical TS and its basic properties, dynamics of the TS, multiple regression in TS, classical model of economical TS (trend, seasonality, long-term cycle), measures of goodness of fit in TS, decomposition of the TS, smoothing in times series context, adaptive modelling, basic principles of spectral analysis and filtering, principles of forecasting, models of financial TS. 4. OPERATION ANALYSIS basic terminology, linear programing, simplex method, projects and net graphs, CPM, PERT, multi-criteria decision analysis, transportation problem mathematical formulation and methods for solving
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Learning activities and teaching methods |
unspecified |
Learning outcomes |
The content of this course is the state final examination in statistics, econometric and decision making theory. Students are required to prove their mastery of basic terminology, theoretical principles and calculation operations in these fields and their correct application in particular problems. The first part of the examination covers topics such a probability and random variables. The second part of the examination covers the basic principles of mathematical statistics and inference. The third part of examination covers some classical method of time series analysis. Finally the fourth part consists of some parts from operation analysis.
Students know basic terminology, theoretical principles, and method used in the field of mentioned subjects. Students are able to apply the acquired knowledge in practice. |
Prerequisites |
Subjects Teorie pravděpodobnosti a statistika (TPS), Statistické modelování a analýza časových řad (SMAC), Ekonometrie (ENM), Operační analýza (OA)
KMI/CENM ----- or ----- KMI/ENM ----- or ----- KMI/KENM ----- or ----- KMI/YENM and KMI/CSMAC ----- or ----- KMI/KSMAC ----- or ----- KMI/SMAC ----- or ----- KMI/YSMAC and KMI/CRM1 ----- or ----- KMI/KRM ----- or ----- KMI/RM ----- or ----- KMI/RM1 |
Assessment methods and criteria |
Oral examination
Students have to prove their complex understanding of the basic terminology and principles of aforementioned quantitative methods; they have to be able to respond to particular questions and to apply theoretical knowledge in practical examples. |
Recommended literature |
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Study plans that include the course |
Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester | |
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Faculty: Faculty of Economics | Study plan (Version): Financial and Insurance Mathematics (4) | Category: Mathematics courses | 3 | Recommended year of study:3, Recommended semester: Summer |