1. SylabUZ
2. Wydział Mechaniczny
3. semestr zimowy 2022/2023
4. Management and Production Engineering - drugiego stopnia z tyt. magistra inżyniera
5. Design of experiments

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Design of experiments - opis przedmiotu

Cel przedmiotu

Knowledge of issues related to the planning of experiments, developing the ability to analyse the results of measurements, using statistical methods of analysis.

Wymagania wstępne

Zapisz zmiany

a course in mathematical statistics

Zakres tematyczny

Lecture:

L1-2: Introduction. Basic concepts: scientific research, experimental research, theory of experiment, experience, active and passive experiment. Classification of experimental plans. Theoretical basis of experimental research. Problem identification and formulation. Choice of response variables. Selection of factors to be varied. Establishing a research method: choice of experimental design, determining the number of replicates. Statistical analysis of the data.

L3-4: Review of problems in mathematical statistics. Statistical distributions and their parameters. Point estimation: measures of central tendency, measures of spread/dispersion and measures of distortion. Data analysis through graphical presentation (histogram, box plot, quantile-quantile plot, normality plot, scatter plot). Hyphotesis testing: inference about the differences in means and goodness-of-fit tests.

L5: Simple comparative experiments. Analysis of the experiments results using of two-Sample t-Test. Checking assumptions: graphical analysis as well as tests for equality of the variances of two populations and goodness-of-fit tests.

L6: Power analysis and calculation minimum sample size. Standarized effect and effect. Determining sample size (umber of replicates).

L7-8: Experiments with a single factor. One-way ANOVA. Checking assumptions. Post-hoc tests. Effect size and measures. Selected measures of the effect. Determining sample size.

L9-10: Experiments with two factors. Factorial designs: main effects and interactions. Two-way ANOVA. Checking assumptions. Post-hoc tests. Determining sample size.

L11: Two and multidimensional random variables.  Measures of dependence among random variables.

l12-13: Regression analysis. Linear Regression. Least squares method. Regression equation quality indicators. Hypothesis testing in multiple regression: test for significance of regression, tests on individual regression coefficients. Checking assumptions - residual analysis.

L14: Stepwise regression. Single factor experiments: relationships between analysis of variance and analysis of regression.

L15: Experimental designs. Full and fractional factorial designs:  two-level, three-level and multi-level. 

Project:

P1-P3: Carrying out a simple comparative experiment. Analysis of experiment results. Checking assumptions. Power analysis. Checking the sample size for the desired effect.

P4-P6: Conducting a two-factor experiment. Analysis of experiment results. Checking assumptions. Power analysis.  Checking the sample size for the desired effect..

P7-P9: Conducting an experiment to develop a model of the selected process. Analysis of experiment results. Checking assumptions.

P10-P12: Presentation of the results.

P13-P14: Verification of solutions - passing the projects.

Metody kształcenia

Lecture: a conventional lecture

Project: a project implemented in groups or individually

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

Lecture: written exam preceded by obtaining a credit for project classes

Project: arithmetic mean of the grades obtained for each project activity

Final grade: the condition for passing the course is to pass all its forms, the final grade for the course is the arithmetic mean of the grades for individual forms of classes

Literatura podstawowa

1. Montgomery D. C., Design and Analysis of Experiments, Wiley, 2012
2. Dean A., Voss D., Draguljić D., Design and Analysis of Experiments, Springer, 2017
3. Hines W. W., Montgomery D. C., Goldsman D. M., Borror C. M., Probability and Statistics in Engineering, Wiley, 2003

Literatura uzupełniająca

1. Toutenburg H., Statistical Analysis of Designed Experiments, Springer, 2002
2. Davim J. P., Design of Experiments in Production Engineering, Springer 2016
3. Wild C. J., Seber G. A. F. , Chance Encounters: A First Course in Data Analysis and Inference, Wiley, 1999

Uwagi

Zmodyfikowane przez dr inż. Tomasz Belica (ostatnia modyfikacja: 25-04-2022 09:38)