| Welcome to DataScope, a web site devoted to the art and science of statistical graphics, with special attention to multivariate data analysis. The web site is also home for materials related to research organization and drug design.
This web-site has been initiated and is maintained by Paul Lewi and Luc Wouters.
Table of Contents
- Drug Design with Dr. Paul Janssen, a multilingual article by Paul Lewi:
- Speaking of Graphics
An ebook on graphicacy in science, technology, and business by Paul Lewi. The book covers the history and development of data visualization methods starting with the Quipu of the Incas and going through to the sophisticated methods of multivariate data analysis.
- Multivariate Data Analysis
A short introduction to multivariate analysis by Paul Lewi, starting from univariate and bivariate methods to factorial data analysis, including principal component analysis, correspondence analysis, and spectral map analysis (also referred to as log-ratio analysis).
- Nonlinear Modeling Application in Experimental Pharmacology
Thesis MSc. Biostatistics L. Wouters
- Graphical exploration of gene expression data: a comparative study of three multivariate techniques
Original version of a manuscript submitted to Biometrics. The article appeared in Biometrics 59, 1133-1141, 2003.
The definitive version of the article is available at the journal site (http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291541-0420)
- Graphical Exploration of Gene Expression Data by Spectral Map Analysis
A presentation held by Luc Wouters at the DIA (Drug Information Association) 3rd International Workshop on Statistical Methodology in Non-Clinical R&D, September 26-27, 2002, Barcelona, Spain.
- Succesful Pharmaceutical Discovery
An article by P. Lewi, submitted to the Journal R&D Management, describing the concept of research organization of Dr. Paul Janssen, founder of Janssen Pharmaceutica. The concept comprises organization around competent people and continuous critical questions.
- Statistical Thinking and Smart Experimental Design (presentation as pdf)
A one day workshop taught at the Flemish Institute for Biotechnology on how statistical thinking permeates the process of biomedical research.
In this one day workshop a conceptual framework is presented that provides insights into the efficient planning, implementation and evaluation of quality experiments.
The research process is considered from a systems analysis point of view in which experimental research is looked upon as an iterative learning process consisting of 4 distinctive but interacting phases:
• definition, asking the right question;
• planning and design;
• analysis and reporting.
Each of these phases is discussed with emphasis on the planning and design stage. While discussing this stage, participants gain insight into major concepts of statistical thinking and their importance for a successful and efficient experiment. In contrast to a technical statistics course, statistical thinking is more involved in asking the right question about the experiment and its conduct. In particular items are discussed such as internal versus external validity, the signal-to-noise ratio, and how to deal in a structured and creative way with bias and variability. In addition, conceptual tools are provided for designing efficient experiments such that bias is eliminated and variability minimized.
The last part of the workshop is about statistical reasoning. This involves the correct interpretation and reporting of the results from the statistical analysis. The workshop is documented with practical examples and ample time is provided for questions and discussion.
The workshop is oriented to researchers with special attention to PhD students and postdocs from all areas of biological research who are interested in the effective and efficient design of quality experiments.
Some documents are in Portable Document Format (PDF) and you will need Acrobat Reader 8.0 or later to view or print the files.
The latest copy of Adobe Acrobat Reader can be downloaded for free from Adobe's web site