Six Sigma Black Belt Exam Prep

Category - Black Belt

Richard builds a predictive model based on data collected from the highway gas mileage of a number of brand name tires. The differences between actual data points and predicted ones are referred to as:
  1. residuals
  2. convergence error
  3. non-response bias
  4. estimators
Explanation
Answer: A - The differences between actual data points and predicted ones are referred to as residuals.

Key Takeaway: Residuals are the differences between actual data points and predicted ones. Predicted data points or responses are usually derived from a predictive model such as that developed from a simple regression model. The larger residuals are, the less likely that the predictive model provides accurate predictions of values.
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