Data transformation (statistics)
From Wikipedia, the free encyclopedia
In statistics, data transformation is carried in order to transform the data and assure that it has a normal distribution (a remedy for outliers, failures of normality, linearity, and homoscedasticity). A good indicator of data having a normal distribution is skewness in the range of -0.8 to 0.8 and kurtosis in range of -3.0 to 3.0.
Common transformation techniques (note that their reflected variants are also used):
 |
This statistics-related article is a stub. You can help Wikipedia by expanding it. |
