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. Relationships between the observations, as well as relationships between the variables will be uncovered by using multivariate techniques.
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
- identify natural groupings in the data via cluster analysis.
Who should attend
Individuals who work with high dimensional data and have a need to identify patterns or groups in the data
Before attending this course, you should complete the JMP Software: Statistical Decisions Using ANOVA and Regression course.
This course addresses JMP software.
