Audience and Purpose:
This course is designed for those Six Sigma professionals who need to understand JMP's
approach to data manipulation and analysis, measurement systems analysis, design of
experiments and statistical process control in direct support of DMAIC breakthrough projects.
Expectations are the participant has a working knowledge of statistics and Six Sigma
concepts.

Course Objectives:
Upon completion of the course the participants will be able to:

1. Understand and apply JMP to Six Sigma breakthrough projects
2. Use JMP for generating and reporting metrics and process capability
3. Determine appropriate sample sizes for studies using JMP
4. Evaluate measurement systems
5. Apply JMP to the manipulation and analysis of data
6. Create appropriate designed experiments using JMP
7. Demonstrate the impact and effectiveness of breakthrough solutions
8. Understand the links and application of JMP to iGrafx process modeling and simulation
9. Develop appropriate process controls using JMP
10. Introduce the participant to JMPs scripting capability

Detailed Course Outline:

Define
Preferences
Table organization and data types
Column commands
Row commands
Table commands
Saving graphs and files

Measure
Establishing project metrics in JMP
Cause and effect diagram
Summary statistics and confidence intervals
Variability studies, contour and surface plots
Sample size selection
Measurement systems analysis for variables
Measurement systems analysis for attributes
Distribution fitting for normal and non-normal data
Process capability analysis
Pareto analysis

Analyze

• Nominal X Continuous Y
  Test mean and standard deviation
  t test - paired
  t test - two sample
  Test for variances
  One-way ANOVA
  Nonparametric tests (optional)
  N-way ANOVA
• Continuous X Continuous Y
  Simple linear regression
  Multiple regression
  ANCOVA
• Nominal X Nominal Y
  Test probabilities
  Contingency analysis
• Continuous X and Nominal Y
  Logistics regression
  iGrafx simulation data in JMP (optional)

Improve

• Design of Experiments
  Full factorial designs
  Screening designs
  Taguchi designs (optional)
  Custom designs
  Augmented designs
  Optimization designs
  Mixture designs (optional)
• Rapid DOE features in iGrafx and JMP (optional)
  
• Evaluating breakthroughs in JMP

Control

• Statistical principles for control charts
  Control charts for variables
  Xbar and R
  Xbar and s
  Individuals and Moving Range
  Presummarize chart
  Delta to target chart
  z chart
• Control charts for attributes
  np
  p
  c
  u
• Creating standard reports and scorecards using JMP scripts