diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.factory.js
index bbae1d68886d..197c64b8b223 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.factory.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.factory.js
@@ -256,11 +256,7 @@ tape( 'the created function evaluates the pdf for `x` given parameters `mu` and
 	for ( i = 0; i < x.length; i++ ) {
 		pdf = factory( mu[i], lambda[i] );
 		y = pdf( x[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			t.ok( isAlmostSameValue( y, expected[i], 1500 ), 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[i], 1500 ), true, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.native.js
index d09db10cc962..d6ed1c4b33bd 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.native.js
@@ -217,11 +217,7 @@ tape( 'the function evaluates the pdf for `x` given parameters `mu` and `lambda`
 	lambda = data.lambda;
 	for ( i = 0; i < x.length; i++ ) {
 		y = pdf( x[i], mu[i], lambda[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			t.ok( isAlmostSameValue( y, expected[i], 1500 ), 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[i], 1500 ), true, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.pdf.js b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.pdf.js
index 8f4098aaba03..bbc8a241051a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.pdf.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.pdf.js
@@ -208,11 +208,7 @@ tape( 'the function evaluates the pdf for `x` given parameters `mu` and `lambda`
 	lambda = data.lambda;
 	for ( i = 0; i < x.length; i++ ) {
 		y = pdf( x[i], mu[i], lambda[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			t.ok( isAlmostSameValue( y, expected[i], 1500 ), 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[i], 1500 ), true, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/test/test.js
index a6263e8951fa..5ca3b00655d7 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/test/test.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/test/test.js
@@ -111,11 +111,7 @@ tape( 'the function returns the skewness of a Wald distribution', function test(
 	lambda = data.lambda;
 	for ( i = 0; i < mu.length; i++ ) {
 		y = skewness( mu[i], lambda[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'mu:'+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			t.ok( isAlmostSameValue( y, expected[i], 20 ), 'within tolerance. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[i], 20 ), true, 'within tolerance. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/test/test.native.js
index 0ffe1e7652d5..e420268ee794 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/test/test.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/test/test.native.js
@@ -120,11 +120,7 @@ tape( 'the function returns the skewness of a Wald distribution', opts, function
 	lambda = data.lambda;
 	for ( i = 0; i < mu.length; i++ ) {
 		y = skewness( mu[i], lambda[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'mu:'+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			t.ok( isAlmostSameValue( y, expected[i], 20 ), 'within tolerance. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[i], 20 ), true, 'within tolerance. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/test/test.js
index 7e8beb938cfd..2152663fad21 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/test/test.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/test/test.js
@@ -111,11 +111,7 @@ tape( 'the function returns the variance of a Wald distribution', function test(
 	lambda = data.lambda;
 	for ( i = 0; i < mu.length; i++ ) {
 		y = variance( mu[i], lambda[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'mu:'+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			t.ok( isAlmostSameValue( y, expected[i], 20 ), 'within tolerance. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[i], 20 ), true, 'within tolerance. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/test/test.native.js
index c0e93eb6774f..5737aa78b199 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/test/test.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/test/test.native.js
@@ -120,11 +120,7 @@ tape( 'the function returns the variance of a Wald distribution', opts, function
 	lambda = data.lambda;
 	for ( i = 0; i < mu.length; i++ ) {
 		y = variance( mu[i], lambda[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'mu:'+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			t.ok( isAlmostSameValue( y, expected[i], 20 ), 'within tolerance. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[i], 20 ), true, 'within tolerance. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' );
 	}
 	t.end();
 });