SubjectsSubjects(version: 850)
Course, academic year 2019/2020
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Experimental Design - NMST436
Title in English: Návrhy experimentů
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018 to 2019
Semester: winter
E-Credits: 5
Hours per week, examination: winter s.:2/2 C+Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Guarantor: doc. RNDr. Zdeněk Hlávka, Ph.D.
Class: M Mgr. PMSE
M Mgr. PMSE > Povinně volitelné
Classification: Mathematics > Probability and Statistics
Pre-requisite : NMST432
Annotation -
Last update: T_KPMS (13.05.2014)
Most basic techniques for the design of experiments.
Aim of the course -
Last update: T_KPMS (13.05.2014)

The aim is to produce students that are able to design experiments.

Course completion requirements -
Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (06.10.2017)

Prerequisites for obtaining the credit (zápočet): participation in the exercises and continuous solving of assigned problems. The nature of the credit does not allow it to be repeated. Acquiring credit is a prerequisite for attending the exam.

Literature - Czech
Last update: T_KPMS (13.05.2014)

Likeš: Navrhování průmyslových experimentů, SNTL 1969.

Neter, Kutner, Nachtsheim, Wasserman: Applied linear statistical models, IRWIN 1996.

Milliken, Johnson: Analysis of messy data: designed experiments. Vol. 1. CRC Press 2009.

Pázman: Základy optimalizácie experimentu, Veda 1980

Pázman, Mikulecká, Raffaj, Tokošová: Riešené situácie z navrhovania experimentov, Alfa 1986.

Pinheiro, Bates: Mixed effects models in S and S-PLUS, Springer 2000.

Zvára: Regrese, Matfyzpress 2008.

Teaching methods -
Last update: T_KPMS (15.05.2013)

Lecture+exercises.

Requirements to the exam -
Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (06.10.2017)

Requirements for the oral exam correspond to the syllabus of the subject in the scope that was presented at the lecture.

Syllabus -
Last update: T_KPMS (13.05.2014)

Planning of sample sizes. Randomized block designs, nested designs, latin square experiments. Factorial designs. Optimality criteria for linear regression models.

Entry requirements -
Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (25.05.2018)

good knowledge of linear regression and mixed models

 
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