Outline & Objectives (302849)
Introduction
Uniqueness of Big Data Projects
-Relative to traditional statistics projects
New Methods for Big Data. What Could Go Wrong?
-Big blunders with Big Data
-Sequential approaches versus one-shot studies
-Integration of analytics with sound subject matter theory
-Data quality
How Statistical Engineering Can Help
-Brief review of statistical engineering
-Theory and key principles
-Building blocks of statistical engineering (major phases)
Application of Statistical Engineering to Big Data
-Discussion
-Breakout exercises
Recap and Summary
-What have we learned?
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