de4004 Applied Mathematical Statistics

Faculty of Sports Studies
spring 2022
Extent and Intensity
0/0/0. 12 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Martin Sebera, Ph.D. (lecturer)
Guaranteed by
Mgr. Martin Sebera, Ph.D.
Department of Kinesiology – Faculty of Sports Studies
Supplier department: Department of Kinesiology – Faculty of Sports Studies
Prerequisites
dc4002 Quantitative Research Method.
Basic knowledge of working with PC (sw Statistica)
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
At the end of this course, students should be able to:
* understand and be able to explain basic statistic characteristics;
* use testing of hypothesis at chosen cases;
* interpret result at real examples (comparing of two groups, finding and description of dependece, evaluation of statistical model;
* use multivariate statistics (Analysis of Variance, Factoral analysis, Multidimensional Regression)
Learning outcomes
Student will be able to:
- identify dependent and independent variables in research, characterize their properties (nominal, categorical, ordinal);
- compare parametric and nonparametric methods;
- describe the hypothesis testing process;
- identify the type of statistical procedure and decide on the used method (comparison of mean values, dependency analysis, classification and regression problem);
- interpret results as the most important part of statistical calculations;
- apply knowledge on data from your dissertation;
Syllabus
  • Basic statistics, selective and data file
  • Punctual and intervallic frequency distribution - histogram
  • Fundamental statistical characteristics
  • Testing hypotheses
  • Kolmogorov-Smirnov, Kruskal-Wallis, F-test, t-test
  • Nonparametrics statistics - Wilcoxon, Mann-Whitney, chi-2
  • Correlation coefficient - Pearson and Spearman correlation coefficient and his testing
  • Regression
  • Analysis of Variance
  • Factoral analysis
  • Multidimensional regression
  • Basic datamining methods
Literature
  • Even You Can Learn Statistics
  • STINEROCK, Robert Noel. Statistics with R : a beginner's guide. First published. Los Angeles: Sage, 2018, xix, 369. ISBN 9781473924901. info
  • JACKSON, Sherri L. Research methods and statistics : a critical thinking approach. Fifth edition. Boston: Cengage Learning, 2016, xx, 508. ISBN 9780357670934. info
  • SEBERA, Martin, Renata KLÁROVÁ and Jiří ZHÁNĚL. Časové řady (Time series). 1. vyd. Brno: Masarykova univerzita, 2014, 53 pp. ISBN 978-80-210-6698-4. info
  • SEBERA, Martin. Statistika - vícerozměrné metody (Statistics - Multivariate methods). první. Brno: Masarykova univerzita, 2014, 97 pp. ISBN 978-80-210-6692-2. info
  • LEVINE, David M. and David STEPHAN. Even you can learn statistics : a guide for everyone who has ever been afraid of statistics. 2nd ed. Upper Saddle River, N.J.: FT Press, 2010, xiv, 370. ISBN 9780137010592. info
  • HENDL, Jan. Přehled statistických metod : analýza a metaanalýza dat. 3., přeprac. vyd. Praha: Portál, 2009, 695 s. ISBN 9788073674823. info
  • MELOUN, Milan and Jiří MILITKÝ. Kompendium statistického zpracování dat : metody a řešené úlohy. Vyd. 2., přeprac. a rozš. Praha: Academia, 2006, 982 s. ISBN 8020013962. info
  • CYHELSKÝ, Lubomír, Jana KAHOUNOVÁ and Richard HINDLS. Elementární statistická analýza. 2. vyd. Praha: Management press, 1999, 319 s. ISBN 8072610031. info
Teaching methods
lectures, class discussion, e-elearning
Work in statistical sw Statistica or SPSS.
Assessment methods
writing test - solving of statistical problem with use of sw (Statistica, SPSS or R), interpretation of results!!!
Language of instruction
English
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: in blocks.
Information on the extent and intensity of the course: 12 hours/term.
Teacher's information
http://www.fsps.muni.cz/impact/aplikovana-matematicka-statistika/
The course is also listed under the following terms spring 2021, spring 2024, spring 2025.
  • Enrolment Statistics (spring 2022, recent)
  • Permalink: https://is.muni.cz/course/fsps/spring2022/de4004