Course unit code:
427M1_4D
Course unit title:
Mathematical Statistics
Mode of completion and Number of ECTS credits:
Exm (6 credits)
Course supervisor:
doc. RNDr. Zdenko Takáč, PhD.
Name of lecturer(s):
Z. Takáč (2021/2022 – Winter)
N. Krivoňáková (2019/2020 – Winter)
Learning outcomes of the course unit:
Get acquainted students with the fundamentals of statistical methods, teach them to handle univariate and multivariate datasets with the assistance of statistical software.
Prerequisites for registration:
none
Course contents:
1. Models of data files - homogeneity (allowance 6/0)
 
a. Models of simple data files -- Analysis of variance
b. Models of multiple data files -- Multi analysis of variance
c. Discriminant analysis

2. Predictions in regression models (allowance 6/0)
 
a. Parametric regression models
b. Nonparametric regression models
c. Regression models with conditions

Recommended or required reading:
Basic:
  • VARGA, Š. Matematická štatistika. Bratsilava : Nakladateľstvo STU, 2012. 219 s. ISBN 978-80-227-3789-0.
  • VOLAUF, P. Matematická štatistika: Zbierka príkladov. Bratislava : STU v Bratislave, 2001. 166 s. ISBN 80-227-1523-9.
  • MONTGOMERY, D C. – RUNGER, G C. Applied Statistics and Probability for Engineers. New York : John Wiley & Sons, 2002. 706 s. ISBN 0-471-20454-4.
Recommended:
  • VARGA, Š. – ŠABO, M. – POSPÍCHAL, J. Matematika III: Matematická štatistika a numerické metódy. Bratislava : STU v Bratislave FCHPT, 2003. 202 s. ISBN 80-227-1840-8.
  • ROUSSAS, G G. A course in mathematical statistics. San Diego : Academic Press, 1997. 572 s. ISBN 0-12-599315-3.
Planned learning activities and teaching methods:
Lectures
Assesment methods and criteria:
Students can obtain 50 points from their homework during the semester, and 50 points from the closing test. Evaluation: A (92-100 points), B (83-91 points), C (74-82 points), D (65-73 points), E (56-64 points), Fx (0-55 points).
Language of instruction:
Slovak, English
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