Europe

Discovery Summit

Exploring Data | Inspiring Innovation

Training

Led by SAS Education instructors, these two-day courses combine lectures, software demonstrations, question-and-answer sessions and hands-on computer workshops for an interactive learning experience. You can sign up for courses at a 20% discount when you register for the conference. Training will be held in the conference hotel, Hilton Amsterdam.

JMP® Software: Analysing Discrete Responses

Date/Time: Monday, 14 March, 9:15-17:00 – Tuesday, 15 March, 9:15-17:00
Location: Orange 2, Hilton Amsterdam
Instructor: Mark Bailey
Standard Price: €1390 plus VAT
Conference Attendee Price: €1112 plus VAT

Course Description: This course teaches you how to analyse discrete, or categorical, data or outcomes using association, contingency tables, stratification, correspondence analysis, logistic regression, generalised linear models, partitioning and artificial neural network models.

Learn how to:
  • Examine associations among variables
  • Perform chi-square and Fisher exact tests
  • Perform stratified analysis
  • Perform correspondence analysis
  • Perform logistic regression
  • Interpret logistic regression output
  • Fit a binary response and a count of events with generalised linear models (GLM)
  • Fit a decision tree model
  • Fit an artificial neural network model

Who Should Attend: Analysts, researchers, technicians, and any others filling similar roles who want to analyse a response with discrete levels or a count of events and who have at least some statistical training

JMP® Software: The Analysis and Modelling of Multidimensional Data

Date/Time: Monday, 14 March, 9:15-17:00 – Tuesday, 15 March, 9:15-17:00
Location: Orange 4, Hilton Amsterdam
Instructor: Di Michelson
Standard Price: €1390 plus VAT
Conference Attendee Price: €1112 plus VAT

Course Description: This course is for JMP users who deal with data with many variables. The course demonstrates various ways to examine high-dimensional data in fewer dimensions, as well as patterns that exist in the data. Methods for unsupervised learning will be presented, in which relationships between the observations, as well as relationships between the variables, will be uncovered. The course also demonstrates various ways of performing supervised learning where the relationships among both the output variables and the input variables are considered. Strong emphasis is on understanding the results of the analysis and presenting your conclusions with graphs.

Learn how to:
  • Use principal components analysis to reduce the number of data dimensions
  • Use loading plots to understand the relationships between variables
  • Interpret principal component scores and perform factor analysis
  • Build more stable models by removing collinearity with principal components regression (PCR)
  • Identify natural groupings in the data via cluster analysis
  • Classify observations into groups with discriminant analysis
  • Fit complex multivariate predictive models with partial least squares (PLS) regression models

Who Should Attend: Individuals who work with high-dimensional data and have a need to identify patterns or groups in the data or have a need to build models to predict response outcome(s) or group assignments.

Event Venue
  • Discovery Summit Europe
  • 14-17 March 2016

Any questions?

SAS Netherlands Training
Email: opleidingen@sas.com
Telephone: +31 35 6996 999