/* -*- mode: d -*-
 * $Id: $
 * http://www.bagley.org/~doug/shootout/
 * from Waldek Hebisch
 */

import string;
import stream;
import random;
import math;

/* kmedian permutes elements of a to get
   a[i]<=a[k] for i<k
   a[i]>=a[k] for i>k
	See. N. Wirth, Algorithms+data structures = Programs
*/

void kmedian(double[] a0, int n, int k) 
{
   double *a = &a[0];
	while (1)
   {  int j = rand() % n; 
      double b = a[j];
		int i = 0;
      j = n - 1;
      while(1)
      {  while( a[i] < b ) i++;
         while( a[j] > b ) j--;
         if(i<j)
         {  double tmp=a[i];
          	a[i]=a[j];
          	a[j]=tmp;
          	i++;
          	j--;
         } 
         else
         {  if(a[j]<b) j++;
            if(a[i]>b) i--;
			   break;
         }
      }

		if(i<k)
      {  k-=i+1;
			n-=i+1;
			a += i+1;
		} 
      else if (j>k)
			n=j;
      else 
         return;
	}
}

double max(double[] a, int n)
{
	int j;
	double temp = a[0];

	for(j = 1; j < n; j++)
   {  if(a[j] > temp)
         temp = a[j];
	}

	return temp;
}


int main()
{
   char line[];
   int i, n = 0, mid = 0;
   double sum = 0.0;
   double mean = 0.0;
   double average_deviation = 0.0;
   double standard_deviation = 0.0;
   double variance = 0.0;
   double skew = 0.0;
   double kurtosis = 0.0;
   double median = 0.0;
   double deviation = 0.0;
   int array_size = 4096;
   
   double[] nums = new double[array_size];
   
   while ((line = stream.stdin.readLine()).length)
   {  sum += (nums[n++] = math.atof(line));
      if (n == array_size)
      {  array_size *= 2;
         nums.length =  array_size;
      }
   }

   mean = sum/n;

   for (i=0; i<n; i++)
   {  double dev = nums[i] - mean;
      double dev2=dev*dev;
      double dev3=dev2*dev;
      double dev4=dev3*dev;
      average_deviation += fabs(dev);
      variance += dev2 /*pow(deviation,2)*/;
      skew += dev3 /* pow(deviation,3) */;
      kurtosis += dev4 /* pow(deviation,4) */;
   }

   average_deviation /= n;
   variance /= (n - 1);
   standard_deviation = sqrt(variance);

   if (variance)
   {  skew /= (n * variance * standard_deviation);
      kurtosis = (kurtosis/(n * variance * variance)) - 3.0;
   }

   mid = (n/2);
   kmedian(nums, n, mid); 
   median = n % 2 ? nums[mid] : (nums[mid] + max(nums,mid))/2;

   printf("n:                  %d\n", n);
   printf("median:             %f\n", median);
   printf("mean:               %f\n", mean);
   printf("average_deviation:  %f\n", average_deviation);
   printf("standard_deviation: %f\n", standard_deviation);
   printf("variance:           %f\n", variance);
   printf("skew:               %f\n", skew);
   printf("kurtosis:           %f\n", kurtosis);
   
   return(0);
}