JMP Software: The Analysis and Modeling of Multidimensional Data
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 are presented, in which relationships between the observations, as well as relationships between the variables are 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
Who should attendIndividuals 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
Before attending this course, you should complete the JMP: Statistical Decisions Using ANOVA and Regression course.
This course addresses JMP software.
Introduction to Multivariate Data