PřF:M6130 Computational statistics - Course Information
M6130 Computational statistics
Faculty of ScienceSpring 2015
- Extent and Intensity
- 2/2/0. 3 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Marie Budíková, Dr. (lecturer)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor) - Guaranteed by
- prof. RNDr. Ivanka Horová, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Thu 10:00–11:50 M1,01017
- Timetable of Seminar Groups:
M6130/02: Thu 16:00–17:50 M6,01011, Thu 16:00–17:50 MP1,01014, P. Ráboňová - Prerequisites
- M7521 Probability and Statistics || M3121 Probability and Statistics I
M7521 or M3121 - Course Enrolment Limitations
- The course is offered to students of any study field.
- Course objectives
- At the end of this course, students - will have a good knowledge of STATISTICA system; - would be able to describe real data sets using tables, statistical graphs and numerical characteristics; - would be able to testing statistical hypothesis using parametrics and nonparametrics tests.
- Syllabus
- Exploratory data analysis:histogram, empirical distribution function, moments, description of time series, multivariate data samples, graphical representation of dependence two or more variables. Nonparametric statistics: rank and rank statistics. Rank tests for one sample. Statistical tests employed with two samples: t-test, F-test, Wilcoxon and sign tests, comparison samples from binomial distributions. Statistical tests employed with three and more samples: ONEWAY, F-test, Kruskal-Wallis test, test of homogeneity for binomial samples. Goodness-of-fit tests: Kolmogorov-Smirnov test, chi-square test. Statistical tests employed with multivariate samples: Pearson's correlation coefficient, Spearman's correlation coefficient.
- Literature
- required literature
- BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Tomáš LERCH. Základní statistické metody. Vydání první. Brno: Masarykova univerzita, 2005, 180 pp. ISBN 80-210-3886. info
- recommended literature
- BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ. Průvodce základními statistickými metodami (Guide to basic statistical methods). vydání první. Praha: Grada Publishing, a.s., 2010, 272 pp. edice Expert. ISBN 978-80-247-3243-5. URL info
- ZVÁRA, Karel. Biostatistika. 1. vyd. Praha: Karolinum, 1998, 210 s. ISBN 8071847739. info
- ANDĚL, Jiří. Statistické metody. 1. vydání. Praha: MATFYZPRESS, 1993, 246 s. info
- CLEVELAND, William S. Visualizing data. Murray Hill: AT & T Bell Laboratories, 1993, 360 s. ISBN 0-9634884-0-6. info
- Teaching methods
- The weekly class schedule consists of 2 hour lecture and 2 hours of class exercises with special statistical software STATISTICA in computer classroom.
- Assessment methods
- During the semester, students write two tests. The examination is written with "open book" and is complemented by practical computer aided data analysis. The examination is scored 100 points. To successfully pass the exam, 51 points will suffice.
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
General note: Jedná se o inovovaný předmět Základní statistické metody.
- Enrolment Statistics (Spring 2015, recent)
- Permalink: https://is.muni.cz/course/sci/spring2015/M6130