Module 7: Experimental Design

Dates - Venue - Description - Target audience - Exam
Course prerequisites - Teacher - Course material - Fees - Enrol

Dates

2 full days: Tuesday March 29 and Thursday March 31, 2016 from 9 am to 4 pm.

Venue

Faculty of Science , Campus Sterre, Krijgslaan 281, Building S9, Ghent

Description

The course content is closely related to the theory and practice of linear statistical models (e.g. regression analysis and analysis of variance).

Although the design phase of a study appears prior to the experimentation and statistical analysis phases, a design is constructed in function of the data analysis that will follow. A good knowledge of the theory of linear statistical models is therefore important.

The key role of experimental design in scientific and operational research is evident. A good design allows for correct interpretation and relevant results of the statistical analysis following the experiment.

Moreover, efficiency in terms of cost versus precision may be considerably increased by choosing an appropriate design.

The aim of this course is not only to teach how to design studies, but also more generally to broaden the understanding of the relation between experimentation and inference.

Some topics that will be addressed:

• General concepts: randomization, blocking and stratification, bias, confounding
• Sample size calculation: exact and approximation methods using simulation
• Optimal designs: methods based on the Fisher information matrix (e.g. A, D and E optimality), orthogonality of a design, designs for parameter estimation versus prediction

Hands-on exercises are worked out behind the PC using the R software.

Target audience

This course targets professionals and investigators from all areas that are involved in designing experiments or are interested in a more profound understanding of how the design of an experiment is related to the data analysis.

Exam

Participants can, if they wish, take part in an exam. Upon succeeding in this test a certificate from Ghent University will be issued to participants with a university degree at the bachelor level or an equivalent degree.

To qualify for reimbursement from the UGent Doctoral Schools one must attend all classes and pass the exam. Additional conditions and procedure.

Course prerequisites

Participants are expected to have an active knowledge of:

• R
• linear regression and ANOVA
• basic matrix algebra

Teacher

Prof. dr. Jan De Neve obtained his PhD in Statistical Data Analysis at
Ghent University and is currently assistant professor at the Department
of Data Analysis at the Faculty of Psychology and Educational Sciences
(Ghent University).

He teaches the course 'Statistiek I' and in the past he had several
teaching duties for both applied and methodological courses (e.g.
Experimental Design, Applied Statistics, Statistical Topics in Food
Technology, Statistics for Genome Analysis, Nonparametric Statistics).

Course material

Copies of lecture notes.

Recommended handbooks (optional):

• Book 1: "Optimal design of experiments: a case study approach", P. Goos and J. Bradley (2011), John Wiley & Sons. ISBN 978-0470744611.
• Book 2: "Design and analysis of experiments", D.C. Montgomery (2008), John Wiley & Sons. ISBN 978-8126540501.

Fees

A different price applies, depending on your main type of employment.

¹ If three or more employees from the same company enrol simultaneously for this course a reduction of 10% on the module price is taken into account.

² AUGent staff and AUGent doctoral students who pay through use of an SAP internal order/invoice can participate at these special rates.

Enrol for this course