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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2024/2025

Design of Experiments

The course is not on the list Without time-table
Code Completion Credits Range
01NEX KZ 4 2+1
Garant předmětu:
Lecturer:
Tutor:
Supervisor:
Department of Mathematics
Synopsis:

For processes of any kind that have measurable inputs and outputs, Design of Experiments (DOE) methods help us in the optimum selection of inputs for experiments, and in the analysis of results. The course consists of selected methods of DOE such as: completely randomized design, randomized block design, Latin squares design and two level factorial experiments.

Requirements:

Basic course of Calculus and Probability (in the extent of the courses 01MAB3, 01MAB4 and 01PRST held at the FNSPE CTU in Prague).

Syllabus of lectures:

1. Introduction to design of experiments and analysis of their results

2. Completely randomized single-factor design: introduction of model with fixed effects, tests of equality of means, choice of the sample size, check of suitability of model, test of equality of variances, transformation to obtain homoscedasticity, model with random effects, estimates of model parameters, and confidence intervals

3. Methods of multiple comparisons: LSD method, Bonferroni method, Scheffé method, Tukey method

4. Randomized block design: definition of model, test of equality of effects, power of test, choice of the sample size, estimate of the lost values

5. Latin and Graeco-Latin squares designs: test of equality of effects, verification of suitability of model, residua, multiple comparisons

6. Two level factorial experiments: statistical models and their properties for 2^2, 2^3 a 2^k designs

Syllabus of tutorials:

1. Statistical hypothesis testing

2. Comparison of several treatment meana - analysis of variance

3. Randomized block design

4. Latin and Graeco-Latin square design

5. Factorial experiments

Study Objective:

Knowledge:

Basic notions and principles of design and analysis of experiments.

Skills:

Application to solution of practical problems, i.e. ability to design an experiment for a concrete problem and to do its statistical evaluation.

Study materials:

Key references:

[1] D. C. Montgomery: Design and analysis of experiments, Wiley 2008

Recommended references:

[2] J. Antony: Design of Experiments for Engineers and Scientists, Butterworth-Heinemann, 2003

Note:
Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-05-18
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