diff --git a/src/distPlus/symbolic/SymbolicDist.re b/src/distPlus/symbolic/SymbolicDist.re
index c3c1b998..d867eb22 100644
--- a/src/distPlus/symbolic/SymbolicDist.re
+++ b/src/distPlus/symbolic/SymbolicDist.re
@@ -100,7 +100,7 @@ module Normal = {
 
   let from90PercentCI = (low, high) => {
     let mean = E.A.Floats.mean([|low, high|]);
-    let stdev = (high -. low) /. 1.645;
+    let stdev = (high -. low) /. (2. *. 1.644854);
     `Normal({mean, stdev});
   };
   let inv = (p, t: t) => Jstat.normal##inv(p, t.mean, t.stdev);
@@ -255,13 +255,29 @@ module GenericSimple = {
     | `Uniform({high}) => high
     | `Float(n) => n;
 
+
+  /* This function returns a list of x's at which to evaluate the overall distribution (for rendering).
+     This function is called separately for each individual distribution.
+
+     When called with xSelection=`Linear, this function will return (sampleCount) x's, evenly
+     distributed between the min and max of the distribution (whatever those are defined to be above).
+
+     When called with xSelection=`ByWeight, this function will distribute the x's such as to
+     match the cumulative shape of the distribution. This is slower but may give better results.
+  */
   let interpolateXs =
       (~xSelection: [ | `Linear | `ByWeight]=`Linear, dist: dist, sampleCount) => {
-    switch (xSelection) {
-    | `Linear => E.A.Floats.range(min(dist), max(dist), sampleCount)
-    | `ByWeight =>
-      E.A.Floats.range(minCdfValue, maxCdfValue, sampleCount)
-      |> E.A.fmap(x => inv(x, dist))
+
+    switch (xSelection, dist) {
+    | (`Linear, _) => E.A.Floats.range(min(dist), max(dist), sampleCount)
+    | (`ByWeight, `Uniform(n)) =>
+      // In `ByWeight mode, uniform distributions get special treatment because we need two x's
+      // on either side for proper rendering (just left and right of the discontinuities).
+      let dx = 0.00001 *. (n.high -. n.low);
+      [|n.low -. dx, n.low +. dx, n.high -. dx, n.high +. dx|]
+    | (`ByWeight, _) => 
+      let ys = E.A.Floats.range(minCdfValue, maxCdfValue, sampleCount)
+      ys |> E.A.fmap(y => inv(y, dist))
     };
   };
 
@@ -379,4 +395,4 @@ let toShape = n =>
   fun
   | `Simple(d) => GenericSimple.toShape(~xSelection=`ByWeight, d, n)
   | `PointwiseCombination(d) =>
-    PointwiseAddDistributionsWeighted.toShape(d, n);
\ No newline at end of file
+    PointwiseAddDistributionsWeighted.toShape(d, n);
diff --git a/yarn.lock b/yarn.lock
index 42114acc..a15e386c 100644
--- a/yarn.lock
+++ b/yarn.lock
@@ -2491,7 +2491,7 @@ bs-moment@0.4.5, bs-moment@^0.4.4:
   resolved "https://registry.yarnpkg.com/bs-moment/-/bs-moment-0.4.5.tgz#3f84fed55c2a70d25b0b6025e4e8d821fcdd4dc8"
   integrity sha512-anPYkFSof+X8EeomnP0fbQBvWFJeganwPqqARVB+fcdKYX2Uog/n3CCiFGEA+66yHbwnWZD5YFhtHCuyLMcQfQ==
 
-bs-platform@7.2.2, bs-platform@^7.2.2:
+bs-platform@7.2.2:
   version "7.2.2"
   resolved "https://registry.yarnpkg.com/bs-platform/-/bs-platform-7.2.2.tgz#76fdc63e4889458ae3d257a0132107a792f2309c"
   integrity sha512-PWcFfN+jCTtT/rMaHDhKh+W9RUTpaRunmSF9vbLYcrJbpgCNW6aFKAY33u0P3mLxwuhshN3b4FxqGUBPj6exZQ==