
Statistical Thinking for Industrial Problem Solving
Course Resources
Statistical Thinking and Problem Solving
For a broad coverage of statistical thinking and problem solving, check out the following books:
- Problem Solving for New Engineers: What Every Engineering Manager Wants You to Know
- Statistical Thinking: Improving Business Performance, 2nd Edition
- Visual Six Sigma: Making Data Analysis Lean, 2nd Edition
Other recommended books related to these topics:
- The Lean Six Sigma Pocket Toolbook
- Out of the Crisis
- The Toyota Way Fieldbook
- The Quality Toolbox, 2nd Edition
- Juran’s Quality Handbook: The Complete Guide to Performance Excellence, 7th Edition
Many useful resources addressing the concepts discussed in this module can be found through simple web searches. Try the suggested search terms below for the following topics:
Problem solving tools — Techniques to identify potential root causes and develop an understanding of the process:
- SIPOC
- Input output mapping
- Brainstorming
- Multi-voting
- Affinity diagram
- Cause and effect diagram
- Cause and effect matrix
- The 5 whys
- Is/is not analysis
- Nominal group technique
- Value stream mapping
Problem definition:
Problem solving methodologies:
- Problem solving method
- Quality improvement in industry
- Quality improvement in manufacturing
- PDCA or PDSA
- DMAIC
- 8D
- Toyota A3
- Six Sigma
- Lean manufacturing
The complete White Polymer case study, including more details about the scenario and the steps the team took to solve the problem, can be found here.
For information on how to import data into JMP, search for "import data" from the JMP Online Documentation home page, or visit the Using JMP outline in the JMP Learning Library for short guides and videos.
Finally, for further inspiration on the value of statistical thinking skills and their potential to transform your organization, read Most Analytics Projects Don’t Require Much Data from the Harvard Business Review.