ISEA

International Statistical Engineering Association

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

For more information watch: JMP Analytically Speaking with Roger Hoerl








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