Course - Statistics and Design of Experiments

For additional information, please check https://www.upf.edu/web/mdm-dtic/course-statistics-and-design-of-experiments The course will start with a brief digression over the several implications that bad statistics have today over the scientific society and why every researcher should know the basic concepts behind a statistical analysis. Session 1: Than the first part of the course will follow introducing General Linear Modelling and its most common applications: F-test, Monofactorial Analysis of Variance (ANOVA) Video https://youtu.be/HFBeIhLVs0U Session 2: In the second class the non-parametric "equivalent" of ANOVA will be introduced: Kruskal-Wallis test. Monofactorial and multifactorial analysis will be presented, together with the definition of Type I and Type II error, multiple comparison errors and tests for multiple comparison. Video https://youtu.be/THcz_pwMl0w Session 3: Projects with more than two factors will be presented. This will lead to the presentation of some examples of Design of Experiment (Latin and Greek-Latin squares) for the reduction of the number of experiments and to the concept of orthonormality. The course will close with the description of linear regression. Video https://youtu.be/LODyiPW1t-o The second part of seminars (videos not available) on statistical analysis is focused over use of ANOVA theory, previously introduced, in order to design campaigns of experiments or of simulations. During the course will be introduced Complete Factorial and Fractional Factorial analysis along with Latin squares and Taguchi methods. The meaning of confounded effects will be introduced along with the generation of analysis blocks. The course will close presenting the Response Surface Methodology.All documents and additional details available at https://www.upf.edu/web/mdm-dtic/course-statistics-and-design-of-experiment