Regression Model Building for Six Sigma and Data Science. Differences and Synergies

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Jul 14 - Jul 14

The presentation of regression modeling and forecasting is analyzed using two approaches:

  1. Parsimonious Statistical Modeling, and
  2. Data Science Model Building.

Forecasting and model adequacy are then compared using real examples with R and Python. Suggestions and implications on the use of Data Science Regression Modeling for Six Sigma projects are discussed.