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diff --git a/math/bevington/fchisq.f b/math/bevington/fchisq.f
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+C FUNCTION FCHISQ.F
+C
+C SOURCE
+C   BEVINGTON, PAGE 194.
+C
+C PURPOSE
+C   EVALUATE REDUCED CHI SQUARE FOR FIT OF DATA 
+C     FCHISQ = SUM ((Y-YFIT)**2 / SIGMA**2) / NFREE
+C
+C USAGE 
+C   RESULT = FCHISQ (Y, SIGMAY, NPTS, NFREE, MODE, YFIT)
+C
+C DESCRIPTION OF PARAMETERS
+C   Y	   - ARRAY OF DATA POINTS
+C   SIGMAY - ARRAY OF STANDARD DEVIATIONS FOR DATA POINTS
+C   NPTS   - NUMBER OF DATA POINTS
+C   NFREE  - NUMBER OF DEGREES OF FREEDOM
+C   MODE   - DETERMINES METHOD OF WEIGHTING LEAST-SQUARES FIT
+C	     +1 (INSTRUMENTAL) WEIGHT(I) = 1./SIGMAY(I)**2
+C	      0 (NO WEIGHTING) WEIGHT(I) = 1.
+C	     -1 (STATISTICAL)  WEIGHT(I) = 1./Y(I)
+C   YFIT   - ARRAY OF CALCULATED VALUES OF Y
+C
+C SUBROUTINES AND FUNCTION SUBPROGRAMS REQUIRED 
+C   NONE
+C
+	FUNCTION FCHISQ (Y,SIGMAY,NPTS,NFREE,MODE,YFIT) 
+	DOUBLE PRECISION CHISQ,WEIGHT
+	DIMENSION Y(1),SIGMAY(1),YFIT(1)
+11	CHISQ=0.
+12	IF (NFREE) 13,13,20
+13	FCHISQ=0.
+	GOTO 40 
+C
+C ACCUMULATE CHI SQUARE 
+C
+20	DO 30 I=1,NPTS
+21	IF (MODE) 22,27,29
+22	IF (Y(I)) 25,27,23
+23	WEIGHT=1./Y(I)
+	GOTO 30 
+25	WEIGHT=1./(-Y(I))
+	GOTO 30 
+27	WEIGHT=1.
+	GOTO 30 
+29	WEIGHT=1./SIGMAY(I)**2
+30	CHISQ=CHISQ+WEIGHT*(Y(I)-YFIT(I))**2
+C
+C	DIVIDE BY NUMBER OF DEGREES OF FREEDOM
+C
+31	FREE=NFREE
+32	FCHISQ=CHISQ/FREE
+40	RETURN
+	END