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Lecture

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In course

PHYS-442: Modeling and design of experiments

In the academic or industrial world, to optimize a system, it is necessary to establish strategies for the experimental approach. The DOE allows you to choose the best set of measurement points to minimize the variance of the results. The concepts learned ...

Instructor

Jean-Marie Fuerbringer

Jean-Marie Fürbringer graduated with a degree in Physics at EPFL in 1987. Developing his doctoral research on sensitivity analysis of simulation models, he was awarded the doctoral degree by EPFL in 1992. From 1995 to 1997, Dr Fürbringer was visiting researcher at the NIST in Gaithersburg (Maryland). In 1997, Dr Fürbringer was appointed visiting professor with the Faculty of Engineering Science at the Catholic University of Lima (PUCP). While at PUCP, he also established and managed the Learning Center of Graña y Montero, which provides training and competency management for the five companies of the group. In 2001, Dr Fürbringer joined the laboratory of production and processes (LGPP) at EPFL where he led and managed several research projects on competency management and engineering education. From 2007 to 2010, he was deputy director of the Institute of Mechanical Engineering. Dr Fürbringer was appointed to the position of deputy dean of the EPFL Doctoral School in 2010 where he has worked till fall 2013. From November 2013 he has been attached to the Section of Physics as research associate.

Official source

https://mediaspace.epfl.ch/media/0_hwrxf7tq

Related concepts (6)

Statistics

Statistics (from German: Statistik, () "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal".

Experiment

An experiment is a procedure carried out to support or refute a hypothesis, or determine the efficacy or likelihood of something previously untried. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Experiments vary greatly in goal and scale but always rely on repeatable procedure and logical analysis of the results. There also exist natural experimental studies.

Statistical significance

In statistical hypothesis testing, a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. More precisely, a study's defined significance level, denoted by , is the probability of the study rejecting the null hypothesis, given that the null hypothesis is true; and the p-value of a result, , is the probability of obtaining a result at least as extreme, given that the null hypothesis is true. The result is statistically significant, by the standards of the study, when .

Design of experiments

The design of experiments (DOE or DOX), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation.

Design