What is Statistical Engineering?
The study of systematic integration of statistical concepts, methods, and tools, often with other relevant disciplines, to solve important problems sustainably.
Why Statistical Engineering?
- Problem solvers are faced with enormous problems such as; Lower cost healthcare, cleaner environment and globally competitive manufacturing.
- Cohesive body of knowledge for solving such problems is lacking.
- Collection and analysis of high quality, relevant data is critical to success.
- Big Data approaches are useful but not sufficient
- Statistical Engineering provides the integration needed to fill the gap.
- Need for Statistical Engineering educational programs and increased published applications of the discipline is vital and urgent.
Core Processes Utilized in Statistical Engineering
- Data acquisition, including surveys and experiments
- Data exploration and visualization
- Model building
- Drawing inferences (learning) from models
- Solution deployment and sustainability
Benefits of Statistical Engineering
- More effective problem solving
- Discipline that can be learned, utilized and enhanced
- Better, more effective use of data
- Sustainability of solutions and results
- Broader understanding and utility of statistical thinking and methods