Course: Multidimensional Statistical Analysis

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Course title Multidimensional Statistical Analysis
Course code KMA/MRSA
Organizational form of instruction Lecture + Exercise
Level of course Bachelor
Year of study not specified
Semester Winter
Number of ECTS credits 4
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Müller Ivo, RNDr. PhDr. Ph.D.
  • Hron Karel, doc. RNDr. Ph.D.
Course content
1 Introduction, classification of methods, elementary notions and problems. 2 Multivariate normal distribution, basic properties. 3 Characterization theorems, conditional normal distribution. 4 Normal regression, partial and multiple correlations. 5 Parameter estimation: unbiased, maximum likelihood. 6 Wishart?s distribution, properties. 7 Transformations of Wishart?s distribution, Hotelling?s statistic. 8 Tests of hypotheses, confidence regions, simultaneous tests. 9 Principal components. 10 Canonical correlations. 11 Discrimination analysis. 12 Factor analysis. Cluster analysis.

Learning activities and teaching methods
Lecture
  • Attendace - 52 hours per semester
  • Preparation for the Course Credit - 22 hours per semester
  • Preparation for the Exam - 50 hours per semester
Learning outcomes
Mastering the principles of multivariate statistical estimation and testing based on normal distributional theory.
Comprehension Mastering the principles of multivariate statistical estimation and testing based on normal distributional theory.
Prerequisites
Motivation to learn

Assessment methods and criteria
Oral exam, Written exam

Credit: active participation in seminars, written test. Exam: oral.
Recommended literature
  • R.C. Rao. (1978). Lineární metody statistické indukce a jejich aplikace. Academia.
  • T.W. Anderson. (1984). An Introduction to Multivariate Statistical Analysis. Wiley.


Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester
Faculty of Science Applications of Mathematics in Economy (2015) Mathematics courses 1 Winter
Faculty of Science Applied Statistics (2015) Mathematics courses 3 Winter
Faculty of Science Applied Mathematics (2014) Mathematics courses 1 Winter