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 Multivariate Data Analysis School

Multivariate Data Analysis School

MDSS		  Click here to download a course outline in Acrobat format Download course outline 
Duration :Duration : 5.0 day(s)		 
 

:: Course Summary

This 5-day course focuses on the practical aspects of the most widely used multivariate methods: Principal Component Analysis (PCA), Factor Analysis, Correspondance Analysis, Cluster Analysis, Discriminant Analysis and Canonical Analysis.

:: Learning Objectives

Upon completion of this course, participants will be able to:
  • Determine which multivariate statistical methods can be used for a given study objective
  • Choose the most appropriate multivariate technique for their data
  • Perform the analysis using their own software
  • Extract the pertinent or relevant information from the output provided by the software
  • Interpret the numerical and graphical results
  • Summarize and communicate the information obtained

    :: Target Audience

    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.

    :: Prerequisite

    To attend this course, participants must have:

  • Completed the course Fundamental Tools in Statistics or an equivalent course
  • A working knowledge of basic concepts in statistics: descriptive statistics (mean, standard deviation, correlation coefficients, etc.), the different types of variables (continuous vs. discrete)

    It is imperative that participants are familiar with the way to carry out data handling/manipulation in their statistical software.

    		•   

    :: Topics Covered

    • A General Overview of Multivariate Methods
      • Why Use Multivariate Methods?
      • What Information Do They Convey?
      • What Type of Data is Required?
    • Basic Ideas and Concepts Underlying Multivariate Statistics
      • Definition of Objects, Variables, Types of Variables, Distances or Similarity between Objects and Variables
    • The following multivariate methods will be covered:
      • Principal Component Analysis
      • Factor Analysis
      • Correspondence Analysis
      • Discriminant Analysis
      • Cluster Analysis
      • Canonical Correlation Analysis

  • Hands-on Exercises and Statistical Software
    Hands-on exercises can be carried out using your own statistical software.
    Participants are encouraged to bring their own laptop and their favorite statistical software to fully harness the power of multivariate data analysis techniques.

  • Assistance During the Exercises and the Use of Statistical Software
    Experienced instructors will be there to assist you. Each instructor has at least 18 years experience with most commonly used statistical software.

  • Examples and Applications
    Examples and applications are taken from various fields: life sciences, social sciences, marketing, business, biotechnology, etc. If you wish, you may bring along your own datasets to work on during the summer school.

    :: Course Content

    This 5-day training course presents the most popular multivariate data analysis methods. A multitude of multidimensional techniques exist and have been developed by several different fields of application: chemometrics, psychology, social sciences, sensory analysis,…
    The course begins with a brief presentation of multivariate techniques, their place among other statistical analysis methods and their historical development.
    Each of the following multivariates technique is presented in detail: Principal Component Analysis (PCA), Factor Analysis, Correspondence Analysis, Cluster Analysis, Discriminant Analysis and Canonical Analysis. Throughout the training, emphasis will be placed on the purpose of each method, the advantages and disadvantages. Moreover, the type of data required for each method and the approach taken by each method will be outlined using examples from several fields of applications.
    In-depth explanation of the graphical software output is provided for each method to ensure a concrete understanding of how these methods work and what they can do.
    For each method, hands-on workshops are provided to give participants the opportunity to assimilate the tools learned using their own software and their own data. This ensures the direct application of these powerful multivariate methods to each individual research problem, enabling participants to extract the most knowledge from the training.

    Photographs of the 2004 Multivariate Summer School held in Knowlton, Quebec

    Hands-on Exercises

    Hands-on Exercises

    Group Photograph

    		•  

    Upcoming Public Sessions
     Location   Date   Language   Seats Left   Price    
     Montreal, Canada   June 16-20, 2008   English   1   CA$2,450.00 
     Register 
     Montreal, Canada   Sept 29-Oct 3, 2008   French   7   CA$2,450.00 CA$2,082.50  
     Register 
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    Offered Discounts

    • Register more than 6 weeks before a session date and get a 15% discount (Displayed above if available).
    • Register 2 persons or more and get a 10% discount (Applied at checkout).
    • Register for 2 sessions or more and get a 10% discount (Applied at checkout).

    Current Reviews
      by Benoit Boulet:
    En tant qu'analyste, je travaille régulièrement avec des ensembles de données que je dois explorer. C'est pourquoi je recherchais une formation statistique appliquée à mes besoins. Nous avions survolé la plupart de ces méthodes d'analyse lors de ma formation universitaire en statistique, mais faute de temps et d'outils avancés, j'avais oublié bien des notions. La semaine de formation de mai 2007 m'a permis de répondre à une foule de questions concernant les différences entre les diverses méthodes et également de m'assurer de bien interpréter les résultats en sortie. J'ai même appris que certaines méthodes peuvent être combinées pour tirer le maximum d'information des données sous étude. Une formation statistique aussi pratique, donnée par des experts en la matière qui savent très bien communiquer, et où l'on peut rapidement mettre en pratique les notions discutées, quelle différence avec l'université! J'ai eu la chance de découvrir également le logiciel XLSTAT (déjà acquis par mon employeur), un outil très puissant, très bien conçu et surtout facile à utiliser. Je m'en sers régulièrement et je ne saurais m'en passer. Ajoutez à cela un groupe de participants de différents domaines d'activités qui n'hésitent pas à échanger et à poser de questions pertinentes et vous avez la recette parfaite pour une semaine de formation des plus enrichissantes! MERCI à vous deux pour cette belle opportunité d'apprentissage que je recommande fortement à toutes les personnes intéressées! Au plaisir de se revoir lors d'une autre formation!
     
      by Betty Sapp:
    The Multivariate Summer School course was extremely well organized and reasonably paced. There was a good balance of instruction and application. I appreciated that instructors built concepts as well as teaching the methods. They were knowledgeable about many stats software packages and therefore able to provide individual instruction for each participant. The fact that they were available for questions and consults during breaks and after class demonstrated their dedication to providing a thorough and worthwhite learning experience. Based on my experience, I would highly recommend this Creascience course.
     
      by Jacquelyn Hill:
    The multivariate data analysis school conducted June 2007 was an excellent learning experience. The overall summary of multivariate methods was very helpful. The background and theory to each multivariate method was presented in an interesting manner. The differences and/or similarities between methods and the advantages/disadvantages, depending upon the application of each method were well-presented. Ample time was allocated to apply the methods on various data sets using the statistical software with which I was most familiar. The instructors are very knowledgeable and proficient with all of the different software packages. Solutions to different types of statistical applications were well-demonstrated and discussed. I was able to draw upon their extensive experience with these programs to improve my own proficiency analyzing data generated from my work.
     
      by Kristine Haggerty:
    The course was excellent and well presented! The opportunity to analyze a variety of interesting sample data sets really enhanced my understanding of the course material and was very helpful. I also enjoyed the chance to try and compare different statistical software packages and I look forward to applying some of the new tools that I learned in my day to day work. Thank you.
     
      by Guy Beauchamp:
    I attended the summer school on multivariate data analysis in 2007 and found the whole experience very satisfying. The instructors were very knowledgeable and the small size of the class allowed everyone to ask questions and receive hands-on support with their own software. The course covered traditionnal methods as well as more recent developments. At the end of the week, I was able to understand the strengths and weaknesses of these approaches and use software to analyse multivariable data.
     
      by Tracey Spinner:
    I had the pleasure to attend the June 25-30, 2006 Multivariate statistics course and before it was even finished, I was recommending it to my colleagues. Coming from a traditional and basic background in statistics, I had no trouble understanding the new material. Infact, the instructors presented the material so it was easy to comprehend and they were able to relate the methods to each of us and our fields. One of my favorite aspects of this course was that it was small and personable. Whenever I needed help, the instructors were always there and teaching me new aspects of my software that I didn't even knew existed. The fact that they knew every statistical software package was also an enormous help and very insightful. I highly recommend this course to anyone who is interested in learning Multivariate statistics, even if they've never been introduced before.
     
      by David Bruce:
    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. David Bruce Hong Kong
     
      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.
     
      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.
     
      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.
     
      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.
     
      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.
     
      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.
     
      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!
     
      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.
     
      by Doulgas 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.

     
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