Minitab: Design of Experiments
Please note prices are subject to change.
Objective: Learn to apply powerful statistical methods for investigating cause-and-effect relationships and improvements for a system or process. Understand comparative hypothesis experiments for making simple comparisons. Spend most of training learning to plan, run and analyze classic fractional or factorial design of experiments to obtain a linear model and key factors for maximizing, minimizing or optimizing a process or desired result. These fractional and factorial designs offer more than "one change at a time" and many other methods of experimentation by accounting for interactions and dependency of multiple factors on an output or result.
What is not covered:
Curvilinear models and response surface DOE (Central Composite and Box-Behnken) will be introduced in training, but is not covered in detail.
However, methods learned in this training can allow one to quickly learn the response surface approach.
If needed, additional training and practice time in curvilinear models and response surface DOE can be added to the training.
Assumption is participants have good Excel computer skills, but have minimal training in basic statistics, DOE and Minitab.
Participants should have portable PCs with Minitab installed (current version is Minitab 17, but earlier versions can be handled by instructor)
Materials: Each student will receive a notebook with course materials and an electronic file with the DOE exercises used in class
Hours: 8:00 a.m. - 4:30 p.m., ½ hour lunch
1. Course Introduction (15 minutes)
2. Introduction to Minitab (45 minutes)
3. Basic Descriptive Statistics: Establishing Your Baseline Measure(s) Before DOE (2.5 hrs)
4. Understanding Confidence Intervals, Hypothesis Testing, Error and Power-Building a foundation for DOE (6 hours)
5. Introduction to Traditional Design of Experiments (1.5 hour)
6. DOE Planning & Design: Most important and difficult part of DOE (4 hrs)
7. Analyzing Your Data, Interpreting Results and Making Predictions (4 hrs)
8. Verifying Your Model or Planning Next Experiment (2 hrs)
9. Practical Exercise: (3 hrs)
There are still openings remaining at this time.