This course, organized by CLAD – Portuguese Association for Classification and Data Analysis, proposes an introduction to Symbolic Data Analysis (ADS), an approach that allows analyzing data that present intrinsic variability, without loss of information by resorting to summary statistics – ie , data whose observations take the form of sets, intervals or distributions, and not real numbers or individual categories, as usual. The techniques presented as application examples will be illustrated using SODAS software and R packages. The program is attached.
All potential users who need or are interested in analyzing data that show variability, e.g., data resulting from the aggregation of individual observations into interest groups or data that represent abstract entities such as biological species or regions as a whole. These techniques are particularly interesting for the fields of economics and management, marketing, social sciences, geography, analysis of official statistics, as well as biology or geology. It is assumed that the participants have solid knowledge of Statistics and Multivariate Data Analysis, in the classical sense.
The course will last 7 hours, from 10:00 to 18:30, with 90 minutes for lunch.
The course will run with a minimum and maximum number of 10 and 20 participants, respectively. Applications not accepted will be sent to future editions of the course. Investment and Application Deadline. For CLAD members (with regularized membership fees) the course is free; the investment for CLAD non-members is €60. CLAD will issue a certificate of participation. The deadline for registration is February 8, 2013.
If you are interested in attending this course, please send the attached registration form to the following e-mail address: email@example.com. The same contact can be used for any other clarifications.
For the Board of CLAD
Fernanda de Sousa
Symbolic Data Analysis Course program
10:00 – 13:00:
Introduction to Symbolic Data Analysis:
– Types of variables and their representation.
– Examples of applications.
– The SODAS package – presentation.
– Visualization of data in SODAS.
– Interfaces: Data aggregation and reading of “native” data.
14:30 – 18:30:
Symbolic data analysis methods:
– Descriptive statistics.
– Analysis in Principal Components.
– Classification Analysis.
– Discriminative Analysis.
– Parametric modeling.