Lectures in course ENG-606: EU EIT Urban Mobility 3-day seminar

Covers the importance of exercises, numerical tools, and iterative problem-solving in DOE.

Multilinear Regression: Design Optimization

Explores multilinear regression, design optimization, ANOVA, model fit, and experimental design.

Explores qualitative factors in experimental design, factorial strategies, model computation, and practical exercises in Matlab.

DOE Qualitative factors III

Explores qualitative factors in Design of Experiments, including Latin squares, factorial designs, and ANOVA tables.

Design Optimisation and Orthogonality: Multilinear Regression

Explores multilinear regression for design optimization and orthogonality, covering teamwork, abstracts, linear and quadratic models, ANOVA, and alias structures.

DOE Qualitative factors: IV

Explores qualitative factors in Design of Experiments, including statistical tests and error types.

Hadamard Design: Introduction and Construction

Introduces Hadamard and Plackett-Burman designs, explaining construction, analysis, and optimization techniques.

Qualitative Factors: Statistical Test and Errors

Covers the computation of effects in Design of Experiments and explains statistical tests and errors, including type I and II errors.

Plackett-Burman Design: Hadamard Matrix

Explores the construction and application of Hadamard matrices for efficient estimation of main effects without interactions in the Plackett-Burman Design.

Multilinear Regression: Basics and Applications

Covers the basics of multilinear regression and its application in analyzing material properties.

Factorial Design: Quantitative Factors

Introduces 2N Full Factorial Design, factorial matrices, main effects, interactions, MATLAB plans, and result analysis.

Factorial design II

Explores the visualization and selection of effects in a 2N Full Factorial Design using the Normal plot method.

Multilinear Regression: Least Square Fit

Covers multilinear regression using least square fit method and the importance of standardizing variables.

Fractional factorial design: Basics and Applications

Explores fractional factorial design basics, including blocking alias, interaction effects, and design comparison.

Multilinear Regression: Standardized Variables and Effects

Explores standardizing variables and effects in multilinear regression analysis.

Multilinear Regression: Least Square Fit

Explores multilinear regression, variance, correlation, optimization, ANOVA, and design procedures.

Fractional factorial design II

Covers the analysis of a 24-1 fractional factorial design and its aliases.

Fractional factorial design: Resolution and Standardized Effects

Explains fractional factorial design principles, focusing on resolution and standardized effects in chemical reactors.

Response Surface Design: Lack of Fit

Explores response surface design, emphasizing lack of fit analysis and quadratic models, with practical examples in Matlab.

Surface Response Designs: II

Explores advanced surface response designs and optimization trade-offs.