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:: Course SummaryThis 3-day session explores the classic and most widely used multivariate methods: Principal Component Analysis (PCA), Factor Analysis, Correspondence Analysis, and Cluster Analysis.:: Learning ObjectivesUpon 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 efficiently:: Target AudienceTargeted toward non-statisticians utilizing statistical methods - researchers, business analysts, graduate students and statisticians interested in an applied workshop, this 3-day course focuses on the practical aspects of the classic and most widely used multivariate methods.:: PrerequisiteTo 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. :: Notes and Other InformationThe format of the training session is unique in many regards:
- Emphasis is put on the objectives of methods, their underlying assumptions and the interpretation of results. Special attention is paid to the generation and interpretation of software output.
- Participants are encouraged to use their own data for exercises.
- They are also invited to use their own software. Featured software include SAS, SPSS, Statistica, Minitab, S-Plus, R, JMP and XLStat*. This provide an opportunity to compare these packages.
- An experienced instructor share his/her knowledge in applying these methods and suggest several original applications.
- Class size is limited to ensure personalized supervision of each participant.
The course venue for the June 2012 edition is Hotel des Coutelliers, a boutique hotel among the top-rated on TripAdvisor, located in the heart of the old city. Note that a few rooms have been reserved for Creascience and are available on a first come-first serve basis at a discounted rate of 110CAD per night (sgl occ. exc. app. tx). Breakfast and a wireless internet connection are included in this price. Alternatively, there are many other accommodation options within walking distance of the course venue.
Registration Deadline: May 15, 2012 | | |
:: 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
- Cluster 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 20 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 training session.:: Course ContentThis 3-day training course explores the classic and most popular multivariate data analysis methods. A wide array 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 role among other statistical analysis methods and their historical development.
Each of the following multivariate techniques is covered in detail: Principal Component Analysis (PCA), Factor Analysis, Correspondence Analysis and Cluster 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.
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