79299 - Design of Experiments

Course Unit Page

  • Teacher Michele Scagliarini

  • Credits 6

  • SSD SECS-S/01

  • Teaching Mode Traditional lectures

  • Language English

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education Affordable and clean energy Industry, innovation and infrastructure Responsible consumption and production

Academic Year 2019/2020

Learning outcomes

The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Particular attention will be paid to: understanding the process of designing an experiment including factorial and fractional factorial designs; examining how a factorial design allows cost reduction, increases efficiency of experimentation, and reveals the essential nature of a process.

Course contents

Introduction to designed experiments.

1. Experiments with a single factor (10 hours)
-The fixed effects model: analysis of variance and regression model
-The random effects model
-The randomized complete bolck design
-Exercises with R

2 Factorial experiments (6 hours)
-The two-factor factorial design with fixed effects: analysis of variance and regression model

3 The 2design (14 hours)
-The 22 design, the 23 design, the general 2k design
-A single replicate of the 2k design
-The addition of center points to the 2k design
-Exercises with R

4 Blocking in a Factorial Design (6 hours)
-Blocking in a Factorial Design
-Examples with R

Readings/Bibliography

Compulsory readings:
D.C. Montgomery (2013) “Design and analysis of experiments”. Eighth Edition. John Wiley and Sons, Singapore.

Recommended readings:
J. Lawson (2015). "Design and Analysis of Experiments with R", Boca Raton: CRC Press, Taylor & Francis Group.

Lecture notes and exam simulations are available on the platform IOL  (https://iol.unibo.it/)

Teaching methods

  • Lectures in a lecturehall and  and practical lessons in a computer laboratory through the R environment.
  • Although attending lessons is not mandatory, it is strongly recommended.

Assessment methods

The assessment aims to evaluate the achievement of the following learning objectives:

  • the knowledge of the design of experiments methodology

  • the ability to design factorial experiments in practical cases

  • In order to take the exam, students are required to put their names down for the exam through Almaesami platform.

In order to take the exam registration is mandatory through Almaesami platform.

The exam is written, and it contains 3 or 4 exercises to complete in two hours.

The evaluation is expressed as a grade of out of 30.

The maximum grade is reached by performing all the assigned exercises perfectly.

The exam is passed if the student reaches a total score of 18/30.

Sufficiency (18/30) can be reached by performing at least half of the assigned exercises.

During the exam it is not allowed to consult textbooks or notes. A pocket calculator is necessary.

Teaching tools

Slides in pdf and R-code for the examples in the computer lab.

Links to further information

http://www.unibo.it/docenti/michele.scagliarini

Office hours

See the website of Michele Scagliarini