The MEAN function computes the mean of a numeric vector. MEAN calls the IDL function MOMENT.
            Tip: You may want to use the RUNNING_STATS function instead, which avoids overflow for large values and also allows you to combine calculations for data sets that do not fit into memory.
            Examples
            x = [65, 63, 67, 64, 68, 62, 70, 66, 68, 67, 69, 71, 66, 65, 70]
result = MEAN(x)
PRINT, result
            IDL prints:
            66.7333
            Syntax
            Result = MEAN( X  
		[, DIMENSION=value]
		[, /DOUBLE] [, /NAN] )
            Return Value
            Returns the average value of a set of numbers.
            Arguments
            X
            An n-element, integer, double-precision or floating-point vector.
            Keywords
            DIMENSION
            Set this keyword to a scalar indicating the dimension across which to calculate the mean. If this keyword is not present or is zero, then the mean is computed across all dimensions of the input array. If this keyword is present, then the mean is only calculated across a single dimension. In this case the result is an array with one less dimension than the input.
            Note: If X only contains one element and DIMENSION=1, then MEAN returns a mean equal to X.
            DOUBLE
            If this keyword is set, computations are done in double precision arithmetic.
            NAN
            Set this keyword to cause the routine to check for occurrences of the IEEE floating-point values NaN or Infinity in the input data. Elements with the value NaN or Infinity are treated as missing data. 
            Version History
            
                
                                 
                    
                        | 5.1 | Introduced | 
                     
                        | 8.0 | Added DIMENSION keyword | 
                    
                        | 9.0 | Allow scalar input to work correctly with DIMENSION=1 | 
                 
            
            See Also
            KURTOSIS, MEANABSDEV, MOMENT, RUNNING_STATS, STDDEV, SKEWNESS, VARIANCE