diff --git a/packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res b/packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res
index e3efe446..03652738 100644
--- a/packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res
+++ b/packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res
@@ -3,6 +3,12 @@ open Expect
 open TestHelpers
 open GenericDist_Fixtures
 
+let klNormalUniform = (mean, stdev, low, high): float =>
+  -.Js.Math.log((high -. low) /. Js.Math.sqrt(2.0 *. MagicNumbers.Math.pi *. stdev ** 2.0)) +.
+  1.0 /.
+  stdev ** 2.0 *.
+  (mean ** 2.0 -. (high +. low) *. mean +. (low ** 2.0 +. high *. low +. high ** 2.0) /. 3.0)
+
 describe("klDivergence: continuous -> continuous -> float", () => {
   let klDivergence = DistributionOperation.Constructors.klDivergence(~env)
 
@@ -63,11 +69,7 @@ describe("klDivergence: continuous -> continuous -> float", () => {
     let prediction = normalDist10
     let answer = uniformDist
     let kl = klDivergence(prediction, answer)
-    let analyticalKl =
-      -.Js.Math.log((10.0 -. 9.0) /. Js.Math.sqrt(2.0 *. MagicNumbers.Math.pi *. 2.0 ** 2.0)) +.
-      1.0 /.
-      2.0 ** 2.0 *.
-      (10.0 ** 2.0 -. (10.0 +. 9.0) *. 10.0 +. (9.0 ** 2.0 +. 10.0 *. 9.0 +. 10.0 ** 2.0) /. 3.0)
+    let analyticalKl = klNormalUniform(10.0, 2.0, 9.0, 10.0)
     switch kl {
     | Ok(kl') => kl'->expect->toBeSoCloseTo(analyticalKl, ~digits=3)
     | Error(err) => {
@@ -122,17 +124,13 @@ describe("klDivergence: mixed -> mixed -> float", () => {
   | (Dist(a''), Dist(b'')) => (a'', b'')
   | _ => raise(MixtureFailed)
   }
-  test("finite klDivergence returns is correct", () => {
+  test("finite klDivergence return is correct", () => {
     let prediction = b
     let answer = a
     let kl = klDivergence(prediction, answer)
     // high = 10; low = 9; mean = 10; stdev = 2
-    let analyticalKlContinuousPart =
-      Js.Math.log(Js.Math.sqrt(2.0 *. MagicNumbers.Math.pi *. 2.0 ** 2.0) /. (10.0 -. 9.0)) +.
-      1.0 /.
-      2.0 ** 2.0 *.
-      (10.0 ** 2.0 -. (10.0 +. 9.0) *. 10.0 +. (9.0 ** 2.0 +. 10.0 *. 9.0 +. 10.0 ** 2.0) /. 3.0)
-    let analyticalKlDiscretePart = -2.0 /. 3.0 *. Js.Math.log(3.0 /. 2.0)
+    let analyticalKlContinuousPart = klNormalUniform(10.0, 2.0, 9.0, 10.0)
+    let analyticalKlDiscretePart = 2.0 /. 3.0 *. Js.Math.log(2.0 /. 3.0)
     switch kl {
     | Ok(kl') =>
       kl'->expect->toBeSoCloseTo(analyticalKlContinuousPart +. analyticalKlDiscretePart, ~digits=0)