Course: Data Analysis in English

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Course title Data Analysis in English
Course code KEM/AAD
Organizational form of instruction Lecture + Tutorial
Level of course Master
Year of study not specified
Semester Summer
Number of ECTS credits 6
Language of instruction English
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Svoboda Milan, Ing. Mgr. Ph.D.
  • Lukáš Ladislav, Doc. RNDr. Ing. CSc.
Course content
- Point estimations, construction of interval estimations. - Asymptotic characteristic of estimations. - Selected tests of statistical hypothesis, ANOVA1, ANOVA2. - Selected non-parametric methods. - Categorical data, Chi-square test for independence. - Tests of goodness of fit, normality tests, K-S test, Chi-square, skewness, kurtosis. - Linear regression, linear model. - Multidimensional linear regression. - Periodic time series and trends, harmonic analysis. - Non-linear regression: one-dimensional, multi-dimensional, introduction to auto-regression. - Quality control.

Learning activities and teaching methods
Lecture supplemented with a discussion, Lecture with practical applications, One-to-One tutorial, Group discussion, Individual study, Students' self-study, Seminar, Practicum
  • Preparation for comprehensive test (10-40) - 40 hours per semester
  • Preparation for an examination (30-60) - 60 hours per semester
  • Presentation preparation (report in a foreign language) (10-15) - 10 hours per semester
  • Contact hours - 52 hours per semester
prerequisite
professional knowledge
Knowledge of: two-semester university course of mathematics; knowledge of statistics course subject matter; knowledge of one semester course of economic statistics.
learning outcomes
The student is able to: - Competently use advanced probability and statistics methods. - For concrete real situations select appropriate method, verify assumptions of its applicability, apply the method correctly and interpret the results back to practice. - With use of probability and statistics perform analysis, synthesis, evaluation and conclusion including quality presentation with notice to limits of probability conclusions.
teaching methods
Lecture supplemented with a discussion
Seminar
Practicum
Group discussion
Students' self-study
Individual study
One-to-One tutorial
Lecture with practical applications
assessment methods
Oral exam
Written exam
Test
Recommended literature
  • DANIEL, W. W., TERRELL, J. C. Business statistics : for management and economics. 7th ed. Boston : Houghton Mifflin Co., 1995. ISBN 0-395-71231-9.


Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester