diff --git a/src/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java b/src/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java
index 49057c13d..fb2825ffc 100644
--- a/src/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java
+++ b/src/java/org/apache/commons/math/stat/regression/AbstractMultipleLinearRegression.java
@@ -139,6 +139,20 @@ public abstract class AbstractMultipleLinearRegression implements
     public double[][] estimateRegressionParametersVariance() {
         return calculateBetaVariance().getData();
     }
+    
+    /**
+     * {@inheritDoc}
+     */
+    public double[] estimateRegressionParametersStandardErrors() {
+        double[][] betaVariance = estimateRegressionParametersVariance();
+        double sigma = calculateYVariance();
+        int length = betaVariance[0].length;
+        double[] result = new double[length];
+        for (int i = 0; i < length; i++) {
+            result[i] = Math.sqrt(sigma * betaVariance[i][i]);
+        }
+        return result;
+    }
 
     /**
      * {@inheritDoc}
diff --git a/src/java/org/apache/commons/math/stat/regression/MultipleLinearRegression.java b/src/java/org/apache/commons/math/stat/regression/MultipleLinearRegression.java
index eb0795b50..34b4c6c46 100644
--- a/src/java/org/apache/commons/math/stat/regression/MultipleLinearRegression.java
+++ b/src/java/org/apache/commons/math/stat/regression/MultipleLinearRegression.java
@@ -59,5 +59,12 @@ public interface MultipleLinearRegression {
      * @return The double representing the variance of y
      */
     double estimateRegressandVariance();
+    
+    /**
+     * Returns the standard errors of the regression parameters.
+     * 
+     * @return standard errors of estimated regression parameters
+     */
+     double[] estimateRegressionParametersStandardErrors();
 
 }
diff --git a/src/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java b/src/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java
index 15431b5b5..4cf271d4e 100644
--- a/src/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java
+++ b/src/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java
@@ -143,6 +143,7 @@ public class OLSMultipleLinearRegression extends AbstractMultipleLinearRegressio
      * @return The beta variance
      */
     protected RealMatrix calculateBetaVariance() {
+        //TODO:  find a way to use QR decomp to avoid inverting XX' here
         RealMatrix XTX = X.transpose().multiply(X);
         return new LUDecompositionImpl(XTX).getSolver().getInverse();
     }
diff --git a/src/test/org/apache/commons/math/stat/regression/OLSMultipleLinearRegressionTest.java b/src/test/org/apache/commons/math/stat/regression/OLSMultipleLinearRegressionTest.java
index 64664c266..97d87deee 100644
--- a/src/test/org/apache/commons/math/stat/regression/OLSMultipleLinearRegressionTest.java
+++ b/src/test/org/apache/commons/math/stat/regression/OLSMultipleLinearRegressionTest.java
@@ -149,8 +149,17 @@ public class OLSMultipleLinearRegressionTest extends MultipleLinearRegressionAbs
                       1E-8);
         
         // Check standard errors from NIST
-        double[][] errors = model.estimateRegressionParametersVariance();
-        //TODO:  translate this into std error vector and check  
+        double[] errors = model.estimateRegressionParametersStandardErrors();
+        TestUtils.assertEquals(new double[] {890420.383607373,
+                       84.9149257747669,
+                       0.334910077722432E-01,
+                       0.488399681651699,
+                       0.214274163161675,
+                       0.226073200069370,
+                       455.478499142212}, errors, 1E-2); // Ugh..
+        // Bad accuracy is in intercept std error estimate.  Could be due to
+        // Current impl inverting XX' to get standard errors.
+        
     }
     
     /**
@@ -245,7 +254,15 @@ public class OLSMultipleLinearRegressionTest extends MultipleLinearRegressionAbs
                 5.4326230830188482,-7.2375578629692230,2.1671550814448222,
                 15.0147574652763112,4.8625103516321015,-7.1597256413907706,
                 -0.4515205619767598,-10.2916870903837587,-15.7812984571900063},
-                1E-12);  
+                1E-12); 
+        
+        // Check standard errors from R
+        double[] errors = model.estimateRegressionParametersStandardErrors();
+        TestUtils.assertEquals(new double[] {6.94881329475087,
+                0.07360008972340,
+                0.27410957467466,
+                0.19454551679325,
+                0.03726654773803}, errors, 1E-10); 
     }
     
     /**