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Sampling Bias results when Samples are collected in such a way that they no longer represent the entire population. Typical sources of bias result from collecting data based on convenience or some preconceived judgements. This can result in data that does not represent the larger population which means decisions based on this data can be equally faulty.

For a better understanding of Sampling Bias and an overview of Lean Six Sigma, check out our Free Lean Six Sigma Yellow Belt Training, Green Belt Training or Lean Training.

Elisabeth Swan

Elisabeth is a Master Black Belt at GoLeanSixSigma.com, the co-author of The Problem-Solver’s Toolkit and co-host of the Just-in-Time Cafe. For over 30 years, she's helped leading organizations like Amazon, Charles Schwab and Marriott International, Inc. build problem-solving muscles with Lean Six Sigma to achieve their goals.
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