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GINI
Returns the sample Gini Excel coefficient, a measure of statistical dispersion.
Syntax
Gini Excel(X)
X
is the input data sample (must be nonnegative) (a one dimensional array of cells (e.g. rows or columns)).
Remarks
 A low Gini Excel coefficient indicates a more equal distribution, with 0 corresponding to complete equality. While higher Gini Excel coefficients indicate more unequal distributions, with 1 corresponding to complete inequality.
 The input data series may include missing values (e.g. #N/A, #VALUE!, #NUM!, empty cell), but they will not be included in the calculations.
 The values in the input data series must be nonnegative.

The Gini Excel coefficient is computed as follows:
Where
 is the input data series () arranged in descending order, so that
 is the number of nonmissing values in the input time series data sample

The Gini Excel coefficient value can range from 0 to 1 and is half the
relative mean difference (RMD).
 is a consistent estimator of the population Gini Excel coefficient, but is generally unbiased (except when the population mean is known).
 Developed by the Italian statistician Corrado Gini in 1912, the Gini coefficient is commonly used as a measure of comparative income or wealth. Where zero (0) corresponds to complete equality and one (1) to complete equality.
Examples
Example 1:
A  B  

1  Date  Data 
2  1/1/2008  #N/A 
3  1/2/2008  1.28 
4  1/3/2008  0.24 
5  1/4/2008  1.28 
6  1/5/2008  1.20 
7  1/6/2008  1.73 
8  1/7/2008  2.18 
9  1/8/2008  0.23 
10  1/9/2008  1.10 
11  1/10/2008  1.09 
12  1/11/2008  0.69 
13  1/12/2008  1.69 
14  1/13/2008  1.85 
15  1/14/2008  0.98 
16  1/15/2008  0.77 
17  1/16/2008  0.30 
18  1/17/2008  1.28 
19  1/18/2008  0.24 
20  1/19/2008  1.28 
21  1/20/2008  1.20 
22  1/21/2008  1.73 
23  1/22/2008  2.18 
24  1/23/2008  0.23 
25  1/24/2008  1.10 
26  1/25/2008  1.09 
27  1/26/2008  0.69 
28  1/27/2008  1.69 
29  1/28/2008  1.85 
30  1/29/2008  0.98 
Formula  Description (Result)  

=GINI($B$2:$B$30)  Gini Excel Coefficient (#VALUE!) 
Files Examples
References
 Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0691042896
 Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0471690740