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Experimental Design - NMST436

Title:	Návrhy experimentů
Guaranteed by:	Department of Probability and Mathematical Statistics (32-KPMS)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2022
Semester:	winter
E-Credits:	5
Hours per week, examination:	winter s.:2/2, C+Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech
Teaching methods:	full-time
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 :	NMSA407
Is interchangeable with:	NSTP179

Opinion survey results Examination dates WS schedule Noticeboard

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