
The BoxCox Transformation is one method of transforming nonnormal data, or data that can not be assumed normal, to meet a normal distribution and allow further capability analysis and hypothesis testing.
The term is named after statisticians George and David Cox which is a method that uses an exponent, Lambda, to transform the data. The value of Lambda is the power to which each data point is raised. Then a new (transformed) set of data is created and that transformed set of data is used in for statistical analysis.
The tool is typically used in the ANALYZE phase of a DMAIC project.
Data Type Assumption:
When the data is not normally distributed, this could result in inaccuracies when calculating a zscore. This could result in an inaccurate representation of your process capability.
Control charts may depict a process that is more or less in control than in reality; and, when performing a hypothesis tests the results of your tests may not be accurate, especially as the data is less normal.
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