MAZRD The processing of real data

Faculty of Science
Spring 2015
Extent and Intensity
0/2. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: k (colloquium).
Teacher(s)
RNDr. Marie Budíková, Dr. (lecturer)
RNDr. Marie Forbelská, Ph.D. (lecturer)
Mgr. Kateřina Pokorová, Ph.D. (assistant)
Mgr. Petra Ráboňová, Ph.D. (assistant)
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
Tue 8:00–9:50 MP2,01014a
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
Course objectives
To acquaint students with problems which appear at real data processing. This subject aims to give a survey of modern statistical methods. At the end of this course the student will be able to apply suitable statistical methods to sets of real data and correctly interpret results of statistical analyses.
Syllabus
  • Types of statistical variables
  • Preparation of real data sets
  • Description of real data sets
  • Graphical representation of data
  • Verification of assumptions of model
  • Parametric and nonparametric tests
  • The analysis of contingency tables
  • Correlation analysis
  • Regression models
  • Generalized linear models
  • Introduction to survival analysis
Literature
    recommended literature
  • PEPE, Margaret Sullivan. The statistical evaluation of medical tests for classification and prediction. Oxford: Oxford University Press, 2004, xvi, 302. ISBN 0198509847. info
  • COLLETT, D. Modelling survival data in medical research. 1st ed. Boca Raton: Chapman & Hall, 1999, xvii, 347. ISBN 0412448904. info
Teaching methods
Lessons are held every week. It consists of lectures followed by statistical data processing using the software STATISTICA respectively R.
Assessment methods
Teams of students will develop projects during the semester. At the end of the semester they will deliver their results in the form of a short presentation in a computer room. Presentations will be assessed as researchers from other scientific areas as teachers of the Institute of Mathematics and Statistics.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2023, Spring 2024.
  • Enrolment Statistics (Spring 2015, recent)
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