diff --git a/src/backend/commands/analyze.c b/src/backend/commands/analyze.c
index f952b3c..b02ac20 100644
--- a/src/backend/commands/analyze.c
+++ b/src/backend/commands/analyze.c
@@ -2575,7 +2575,8 @@ compute_scalar_stats(VacAttrStatsP stats,
 		 * the MCV list is not complete, it's generally worth being more
 		 * selective, and not just filling it all the way up to the stats
 		 * target.  So for an incomplete list, we try to take only MCVs that
-		 * are significantly more common than average.
+		 * are significantly more common than average frequency for values which
+		 * will not be represented in the MCV list.
 		 */
 		if (track_cnt == ndistinct && toowide_cnt == 0 &&
 			stats->stadistinct > 0 &&
@@ -2587,6 +2588,7 @@ compute_scalar_stats(VacAttrStatsP stats,
 		else
 		{
 			double		ndistinct_table = stats->stadistinct;
+			double		values_cnt_remaining = (double) values_cnt;
 			double		avgcount,
 						mincount,
 						maxmincount;
@@ -2594,25 +2596,27 @@ compute_scalar_stats(VacAttrStatsP stats,
 			/* Re-extract estimate of # distinct nonnull values in table */
 			if (ndistinct_table < 0)
 				ndistinct_table = -ndistinct_table * totalrows;
-			/* estimate # occurrences in sample of a typical nonnull value */
-			avgcount = (double) nonnull_cnt / ndistinct_table;
-			/* set minimum threshold count to store a value */
-			mincount = avgcount * 1.25;
-			if (mincount < 2)
-				mincount = 2;
-			/* don't let threshold exceed 1/K, however */
-			maxmincount = (double) values_cnt / (double) num_bins;
-			if (mincount > maxmincount)
-				mincount = maxmincount;
-			if (num_mcv > track_cnt)
-				num_mcv = track_cnt;
-			for (i = 0; i < num_mcv; i++)
-			{
+			/* estimate # of occurrences in sample of a typical nonnull value */
+  			for (i = 0; i < num_mcv; i++)
+  			{
+				avgcount = values_cnt_remaining / ndistinct_table;
+				/* set minimum threshold count to store a value */
+				mincount = avgcount * 1.25;
+				if (mincount < 2)
+					mincount = 2;
+				/* don't let threshold exceed 1/K, however */
+				maxmincount = (double) values_cnt / (double) (num_bins);
+				if (mincount > maxmincount)
+					mincount = maxmincount;
+				if (num_mcv > track_cnt)
+					num_mcv = track_cnt;
 				if (track[i].count < mincount)
 				{
 					num_mcv = i;
 					break;
 				}
+				values_cnt_remaining -= track[i].count;
+				ndistinct_table--;
 			}
 		}