subroutine confls(x2sum,n,level)
c ---- x2sum  -- sum of the squares of the standard normal deviates.
c ---- n      -- number of deviates (degrees of freedom)
c ---- level  -- level at which one can be sure the sample of deviates
c                 is DIFFERENT FROM the parent population.
c
      real x2sum,level
      integer n
c ---- For ACM routines:
      double precision bound,df,p,q,x
      integer status,which
      data which /1/
      x = dble(x2sum)
      df = dble(n)
c
c    A confidence interval on the *Standard Normal* sample varience.
c    Returns the "level" (percent) at which one can be confident
c    that the sample of 'N' measurements which produced X2sum, came
c    from a population DIFFERENT FROM a population with mean=0.0,
c    and variance=1.0 .  Note that this is a test of the sample
c    varience only -- it does not involve or test the sample mean.
c
c    Generally:
c             / Xi - mu \ 2       2
c        Sum  | ------- |     ~  X (N); ie, Chi-Square(N)
c             \  sigma  /
c
c    But for our purposes, since mu=0 and sigma=1, this reduces to:
c
c            /  2\      2
c        Sum \Xi /  ~  X (N); ie, Chi-Square(N)
c
c    Written 05/02/00 -- C. R. Meyer
c    Rewritten 5/16/00 to utilize Chi-Square routines from Numerical Recipes
c    --- CRM
c
      if(n .gt. 0) then
c ------- LEVEL is a decimal fraction here:
c ------- To use binary "chi-sq.o" from copyrighted Numerical Recipes:
c       level = gammp(float(n)/2.0,x2sum/2.0)
c ------- To use public domain ACM code (below):
        call cdfchi(which,p,q,x,df,status,bound)
        level = p
c ------- LEVEL is a percent here:
        level = 100.0 * 2.0*abs(0.5 - level)
      else
        level = 0.0
      endif
c
      return
      end