An applied set of modules with focus on the most widely used multivariate methods and their applications in several fields of application. Learn about the principle of the methods, the data needed, and the information they provide.
Multivariate Data Analysis School
Upon completion of this module, participants will be able:
- To determine which multivariate statistical methods can be used for a given study objective
- To choose the most appropriate multivariate technique for their data
- To perform the analysis using their own software
- To extract the pertinent or relevant information from the output provided by the software
- To read and interpret numeric and graphical software output
- To report and communicate the results of the analyses
Targeted toward non-statisticians who use statistical methods - researchers, sensory 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.
Knowledge of basic principles of descriptive analysis is recommended.
- A General Overview of Multivariate Methods
- Classical Multivariate Methods
- Principal Component Analysis (PCA)
- Factor Analysis
- Simple & Multiple Correspondence Analysis
- Discriminant Analysis
- Cluster Analysis
- Overview of Advanced Multivariate Methods
- Case Studies
Recommended Course Duration: 4-5 days
posted by Douglas Hillshafer
The June 19 - 24, 2005 Multivariate summer school was a model for how training sessions should be conducted. Everything, from the logistics of how and where the session was run to the topics covered and practical experience met my expectations.
In fact, I have recommended this training for several of my colleagues.
posted by MaryAnn Filadelfi-Keszi
The June 19 - 24, 2005 Multivariate summer school was six days well spent. The instructors were highly knowledgeable and they presented the subject matter very well. It was at an easy pace and in plain english, no unnecessary formulas to confuse non-mathematicians. Thank you.
posted by Ajay Babar
Had the opportunity to attend the 5 day Multivariate Data Analysis Summer School in June 2005.
The course had an applied focus backed by an adequate amount of theoretical briefing for non-statisticians. Besides, covering the established (traditional) multivariate procedures the course also covered newer techniques like the Principal Component Regression (PCR) and Partial Least Squares (PLS).
The other strong point on this course was the hands-on application using SAS 9.1. An added bonus was learning to use XLStat (an excel add-on) to do multivariate analysis.
Excellent course material delivered by statisticians with exceptional industry background.
Would recommend this course without any reservations!
posted by Deborah Roberts
The June 19 - 24, 2005 Multivariate summer school was an excellent course, especially as the instructors were able to answer everyone's specific questions while keeping the course general for all. They were very knowledgeable, patient, and well-organized with the course and materials. Personally, I got a lot out of the course that I can directly use in my work.
posted by William Melay
I attended the multivariate Data Analysis Summer School from June 19th-24th, 2005. Overall, I found the material very well organized and presented, knowledgeable instructors and staff who gave relevant examples to illustrate the various techniques. Ample time was provided for hands on application with the user's statistical software of choice. The introduction of XLstat also aided in the learning process, as it seemed the most versatile of all the software packages used. As well, the course was a great opportunity to view datasets from multiple disciplines and backgrounds, this allowed for a free exchange of ideas to find an efficient solution to common problems. All and all, it was a great learning experience that I would highly recommend to anyone wishing to enhance their knowledge and abilities with Statistical data analysis.
posted by Marieke Sassen
I attended the 5 day Multivariate Data Analysis course in June 2005. The course was very well organized and the course leaders were very knowledgeable about the subject as well as different software packages. They were a great help with formatting some of my data for analysis. The course gave a very good and very practical overview of methods and their applications. There was ample time to practice with one's own data and statistical software. I learned a lot in a relatively short time and I would recommend this course to anyone interested in learning about multivariate data analysis.
posted by Fahad Al-Sheetan
I attended the 5 day Multivariate Data Analysis course in September 2005. The course was very well organized and it gave a very good and very practical overview of methods and their applications. The lecturer is very knowledgeable about the subject as well as different software packages and she was able to answer everyone's specific questions while keeping the course general for all. I would recommend this course to anyone interested in learning about multivariate data analysis in general.
posted by Anupun Terdwongworakul
I attended the 5 day Multivariate Data Analysis course in September 2005. It was a training course with consultation nature. The emphasis was placed on how to interpret the analyzed results. You would learn the differences among each techniques and soon realized which technique suited your need for analysis. The trainer attitude towards the participants was so nice that the course went smoothly and everyone could follow the contents very well.
Certainly it was highly recommended for everyone interested in the topic.
posted by Stephen Woody
The Multivariate Data Analysis Summer School is an excellent course. The focus is on what the different multivariate techniques can be used for, the assumptions and potential pitfalls, and understanding the output of the statistical software. The underlying statistical theories of each technique are touched on just enough to keep you out of trouble without overwhelming you with equations. The fact that you are using your own software package is a big plus since you can immediately apply what you learned when you return to your office instead of having to figure out how to use your software.
posted by David Bruce, Hong Kong
26-30 June 2006, Montreal, English
For someone studying for a PhD, needing knowledge of multi-variate statistical analysis, without access to in-house University programs, this course was a welcomed immersion into the world of quantitative analysis. While subsequent private study is inevitable, the course does an excellent job in setting the scene and providing road signs for further study.