# Empirical Cumulative Distribution Transform

Menu location: **Data_Transforming and Deriving_Common Transforms_Empirical Cumulative Distribution**.

This function takes a variable and returns its cumulative distribution function in a column marked with the label ECDF:<name> where <name> is the column label of the original data.

The ECDF is a simple step function that jumps k/n at each unique member of an ordered set of n data points, where k is the number of ties (observations with the same value). So, for a set of observations x(1...n), the ECDF Fn(t) is the fraction of observations less than or equal to t.

The ECDF is an unbiased and maximum likelihood estimator of the theoretical CDF of the process generating the data, so it plays an important role in many statistical methods.

__Example__:

Data A, become ---> | ECDF: Data A |

1 | 0.16667 |

3 | 0.33333 |

5 | 0.66667 |

4 | 0.5 |

7 | 0.83333 |

9 | 1 |