MA012 Statistics II

Faculty of Informatics
Autumn 2019
Extent and Intensity
2/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
Teacher(s)
Mgr. Ondřej Pokora, Ph.D. (lecturer)
Mgr. et Mgr. Daniela Kuruczová, Ph.D. (seminar tutor)
Guaranteed by
Mgr. Ondřej Pokora, Ph.D.
Department of Computer Science – Faculty of Informatics
Supplier department: Faculty of Science
Timetable
Thu 16:00–17:50 A217
  • Timetable of Seminar Groups:
MA012/T01: Wed 18. 9. to Sun 22. 12. Wed 10:00–11:50 A420, Thu 19. 9. to Sun 22. 12. Thu 9:00–10:40 115, D. Kuruczová, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
MA012/01: Mon 8:00–9:50 A215, O. Pokora
MA012/02: Wed 14:00–15:50 A215, D. Kuruczová
MA012/03: Wed 16:00–17:50 A215, D. Kuruczová
Prerequisites
Prerequisites: calculus in one and several variables, basics of linear algebra, probability and statistics from course MV011 Statistics I.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 25 fields of study the course is directly associated with, display
Course objectives
Course will introduce advanced statistical methods and usage of freely available software tool R.
Learning outcomes
Upon completing this course, students will be able: to apply advanced statistical method for real datasets; to understand the corresponding algorithms and calculations; to statistically analyze multivariate data; to employ the free statistical software R.
Syllabus
  • One- and two-factor analysis of variance (ANOVA);
  • Nonparametric statistical tests;
  • Goodness-of-fit tests;
  • Multivariate linear regression;
  • Correlation analysis, coefficients of correlation;
  • Autocorrelation, multicollinearity;
  • Generalized linear models (GLM);
  • Principal component analysis (PCA);
  • ROC curves, decision-making;
Literature
  • ANDĚL, J. Základy matematické statistiky. Praha: MFF UK, 2005. info
  • RAO, C. Radhakrishna. Lineární metody statistické indukce a jejich aplikace. Translated by Josef Machek. Vyd. 1. Praha: Academia, 1978, 666 s. URL info
  • BERNSTEIN, Stephen and Ruth BERNSTEIN. Schaum's outline of theory and problems of elements of statistics : descriptive statistics and probability. New York, N.Y.: McGraw-Hill, 1999, vii, 354. ISBN 0070050236. info
  • ANDĚL, Jiří. Statistické metody. 1. vyd. Praha: Matfyzpress, 1993, 246 s. info
Teaching methods
Lectures, Exercises
Assessment methods
The weekly class schedule consists of 2 hour lecture and 2 hours of class exercises. Throughout semester, students fill in question sets and solve practical task in R. The examination is written with short oral discussion on student's project. At least 50 % of the total points are required for successful completiton of the course.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
The course is also listed under the following terms Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2019, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2019/MA012