diff --git a/src/java/org/apache/commons/math/special/Beta.java b/src/java/org/apache/commons/math/special/Beta.java
index ebbc3678f..cbeb0c4ca 100644
--- a/src/java/org/apache/commons/math/special/Beta.java
+++ b/src/java/org/apache/commons/math/special/Beta.java
@@ -60,7 +60,7 @@ import org.apache.commons.math.util.ContinuedFraction;
  * This is a utility class that provides computation methods related to the
  * Beta family of functions.
  * 
- * @version $Revision: 1.12 $ $Date: 2003/11/14 22:22:17 $
+ * @version $Revision: 1.13 $ $Date: 2003/11/18 15:07:12 $
  */
 public class Beta {
     /** Maximum allowed numerical error. */
@@ -151,8 +151,11 @@ public class Beta {
         double ret;
 
         if (Double.isNaN(x) || Double.isNaN(a) || Double.isNaN(b) || (x < 0) ||
-            (x > 1) || (a <= 0.0) || (b <= 0.0)) {
+            (x > 1) || (a <= 0.0) || (b <= 0.0))
+        {
             ret = Double.NaN;
+        } else if (x > (a + 1.0) / (a + b + 1.0)) {
+            ret = 1.0 - regularizedBeta(1.0 - x, b, a, epsilon, maxIterations);
         } else {
             ContinuedFraction fraction = new ContinuedFraction() {
                 protected double getB(int n, double x) {
diff --git a/src/java/org/apache/commons/math/stat/BivariateRegression.java b/src/java/org/apache/commons/math/stat/BivariateRegression.java
index 871c8dd1b..70015e522 100644
--- a/src/java/org/apache/commons/math/stat/BivariateRegression.java
+++ b/src/java/org/apache/commons/math/stat/BivariateRegression.java
@@ -84,7 +84,7 @@ import org.apache.commons.math.distribution.TDistribution;
  * the necessary computations to return the requested statistic.</li>
  * </ul>
  *
- * @version $Revision: 1.9 $ $Date: 2003/11/15 16:01:38 $
+ * @version $Revision: 1.10 $ $Date: 2003/11/18 15:07:12 $
  */
 public class BivariateRegression {
     
@@ -133,11 +133,13 @@ public class BivariateRegression {
             xbar = x;
             ybar = y;
         } else {
-            sumXX += ((double) n / (double) (n + 1)) * (x - xbar) * (x - xbar);
-            sumYY += ((double) n / (double) (n + 1)) * (y - ybar) * (y - ybar);
-            sumXY += ((double) n / (double) (n + 1)) * (x - xbar) * (y - ybar);
-            xbar += (1d / (double) (n + 1)) * (x - xbar);
-            ybar += (1d / (double) (n + 1)) * (y - ybar);
+            double dx = x - xbar;
+            double dy = y - ybar;
+            sumXX += dx * dx * (double) n / (double) (n + 1.0);
+            sumYY += dy * dy * (double) n / (double) (n + 1.0);
+            sumXY += dx * dy * (double) n / (double) (n + 1.0);
+            xbar += dx / (double) (n + 1.0);
+            ybar += dy / (double) (n + 1.0);
         }
         sumX += x;
         sumY += y;
diff --git a/src/test/org/apache/commons/math/stat/BivariateRegressionTest.java b/src/test/org/apache/commons/math/stat/BivariateRegressionTest.java
index 41fbdb599..6c35ce4c8 100644
--- a/src/test/org/apache/commons/math/stat/BivariateRegressionTest.java
+++ b/src/test/org/apache/commons/math/stat/BivariateRegressionTest.java
@@ -53,13 +53,15 @@
  */
 package org.apache.commons.math.stat;
 
+import java.util.Random;
+
 import junit.framework.Test;
 import junit.framework.TestCase;
 import junit.framework.TestSuite;
 /**
  * Test cases for the TestStatistic class.
  *
- * @version $Revision: 1.8 $ $Date: 2003/11/14 22:22:18 $
+ * @version $Revision: 1.9 $ $Date: 2003/11/18 15:07:12 $
  */
 
 public final class BivariateRegressionTest extends TestCase {
@@ -258,6 +260,35 @@ public final class BivariateRegressionTest extends TestCase {
            ;
        }
        
-    }                                        
+    }
+    
+    public void testPerfect() {
+        BivariateRegression regression = new BivariateRegression();
+        int n = 100;
+        for (int i = 0; i < n; i++) {
+            regression.addData(((double) i) / (n - 1), i);
+        }
+        assertEquals(0.0, regression.getSignificance(), 1.0e-5);
+        assertTrue(regression.getSlope() > 0.0);
+    }
+    
+    public void testPerfectNegative() {
+        BivariateRegression regression = new BivariateRegression();
+        int n = 100;
+        for (int i = 0; i < n; i++) {
+            regression.addData(-((double) i) / (n - 1), i);
+        }
+        assertEquals(0.0, regression.getSignificance(), 1.0e-5);
+        assertTrue(regression.getSlope() < 0.0);
+    }
+    
+    public void testRandom() {
+        BivariateRegression regression = new BivariateRegression();
+        Random random = new Random(1);
+        int n = 100;
+        for (int i = 0; i < n; i++) {
+            regression.addData(((double) i) / (n - 1), random.nextDouble());
+        }
+        assertTrue(0.0 < regression.getSignificance() && regression.getSignificance() < 1.0);
+    }
 }
-