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Date: February 26th 2007

2007 Edition of the Multivariate Data Analysis School

For the fourth consecutive year, we are proud to invite you to attend our multivariate data analysis school. This year, the English language session has been scheduled in Montreal from June 18 to 22, 2007.

Targeted toward non-statisticians utilizing statistical methods - researchers, business analysts, graduate students - and statisticians interested in an applied workshop, this 5-day course focuses on the practical aspects of the most widely used multivariate methods: Principal Component Analysis (PCA), Factor Analysis, Correspondence Analysis, Cluster Analysis, Discriminant Analysis and Canonical Analysis. Applications in a variety of fields are presented (business, marketing, R&D) and related methods specific to these fields are also discussed.

The format of our school is unique in many regards:

Emphasis is put on the objectives of methods, their underlying assumptions and the interpretation of results
A special attention is paid to the generation and interpretation of computer output
Participants may use their own data for exercises
Participants are invited to use their own software. Featured software include SAS, SPSS, Statistica, Minitab, S-Plus, JMP and XLStat*. The workshop also provides an opportunity to compare these packages.
Experienced instructors share their knowledge in applying these methods and suggest many original applications.
Basic ideas and concepts of statistics and statistical thinking are introduced, explained, and connected with contemporary applications of statistical methods

Follow this link to get more details on this session, including the course outline, the registration fees, the number of seats left and to register to the workshop. This web page also provides feedback from previous attendees. Do not hesitate to contact us for any question you might have.

*If you are using another software package and want to attend the training session, please contact us..

Upcoming sessions

Analysis of Variance

Location: Montreal
Date: March 5, 2007

The focus of this one-day workshop is to present the available tools to compare two groups or more on a continuous or quantitative measurement variable. In the simplest situation where two groups need to be compared, the classical Student test (or t-test) is first covered. More complex cases are then discussed: the t-test to compare two related samples, the one-way ANOVA, and ANOVA for several factors and interactions. Moreover, multiple comparisons techniques are discussed to locate group differences. Throughout the session, emphasis is put on the conditions of use for each technique, the type of results obtained and their interpretation. A variety of case studies are used to exemplify situations likely to occur in practice, the typical problems and remedial measures.

Get more info and register.

Design & Analysis of Shelf-Life & Stability Studies

Location: Chicago, USA
Date: May 21, 2007

This one-day workshop uses a variety of case studies to present the most important aspects to consider for a sound determination of product shelf life.
Starting from the assessment of the differences between shelf-life and stability studies, participants learn for each type of study how to design efficient experiments to determine the failure time of products accurately. The issues discussed include the timepoint selection, how to handle destructive testing, the experiment size and the choice of samples.
The workshop also emphasizes the appropriate ways to analyze life data and to adequately interpret and communicate the results obtained. The principle of accelerated shelf-life testing (ASLT) along with the conditions for a successful use are discussed.

Get more info and register.

Fundamental Tools in Statistics

Location: Chicago, USA
Date: May 22, 2007

This 1-day hands-on workshop offers an introduction to the fundamental principles and concepts in statistics.
The first part covers classical and more recent exploratory data analysis (EDA) techniques to describe data with numerical and graphical tools. The various uses of these methods like outlier detection is presented. The second part addresses, with the help of real-life examples, the principles underlying statistical testing and decision-making in the presence of uncertainty. It covers risks involved (alpha and beta), p-values and statistical significance. The use and interpretation of confidence intervals are also discussed.
This course can serve as an introductory class or a refresher and provides a solid basis for all other courses.

Get more info and register.

Introduction to the Design of Experiments

Location: Chicago, USA
Date: May 23-24, 2007

This 2-day hands-on workshop presents classical techniques to design efficient experiments as well as the tools to analyze their results. The principles of sample size calculations, strategies to remove undesirable sources of variability like the use of blocks and controls, as well as the most commonly used experimental designs are discussed. The statistical analysis of designed experiments is progressively introduced, starting with the t-test method used to compare two groups. Then, the analysis of variance technique (ANOVA) is extensively covered from simple one-factor experiments to more advanced multi-factor situations where the interaction between factors needs to be considered. Multiple comparisons techniques used to locate differences are also presented.

Get more info and register.

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