diff --git a/lib/node_modules/@stdlib/stats/ttest2/test/test.js b/lib/node_modules/@stdlib/stats/ttest2/test/test.js
index cb937db7db48..60a3fca11df0 100644
--- a/lib/node_modules/@stdlib/stats/ttest2/test/test.js
+++ b/lib/node_modules/@stdlib/stats/ttest2/test/test.js
@@ -22,10 +22,9 @@
 
 var tape = require( 'tape' );
 var contains = require( '@stdlib/assert/contains' );
-var abs = require( '@stdlib/math/base/special/abs' );
+var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 var ttest2 = require( './../lib' );
 
 
@@ -180,9 +179,7 @@ tape( 'the function throws an error if the `alpha` option is a numeric value out
 
 tape( 'the function by default performs a Welch two-sample t-test assuming unequal population variances', function test( t ) {
 	var expected;
-	var delta;
 	var out;
-	var tol;
 	var a;
 	var b;
 
@@ -192,33 +189,23 @@ tape( 'the function by default performs a Welch two-sample t-test assuming unequ
 
 	// Tested against R:
 	expected = unequal.pValue;
-	delta = abs( out.pValue - expected );
-	tol = 18.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. pValue: '+out.pValue+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.pValue, expected, 17 ), true, 'returns expected value' );
 
 	expected = unequal.statistic;
-	delta = abs( out.statistic - expected );
-	tol = 1.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. statistic: '+out.statistic+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.statistic, expected, 0 ), true, 'returns expected value' );
 
 	expected = unequal.lower;
-	delta = abs( out.ci[0] - expected );
-	tol = 16.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. lower CI: '+out.ci[0]+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.ci[0], expected, 0 ), true, 'returns expected value' );
 
 	expected = unequal.upper;
-	delta = abs( out.ci[1] - expected );
-	tol = 1.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. upper CI: '+out.ci[1]+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.ci[1], expected, 1 ), true, 'returns expected value' );
 
 	t.end();
 });
 
 tape( 'the function performs a two-sample t-test assuming equal population variances if `variance` option is set to `equal`', function test( t ) {
 	var expected;
-	var delta;
 	var out;
-	var tol;
 	var a;
 	var b;
 
@@ -230,33 +217,23 @@ tape( 'the function performs a two-sample t-test assuming equal population varia
 
 	// Tested against R:
 	expected = equal.pValue;
-	delta = abs( out.pValue - expected );
-	tol = 2.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. pValue: '+out.pValue+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.pValue, expected, 1 ), true, 'returns expected value' );
 
 	expected = equal.statistic;
-	delta = abs( out.statistic - expected );
-	tol = 4.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. statistic: '+out.statistic+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.statistic, expected, 0 ), true, 'returns expected value' );
 
 	expected = equal.lower;
-	delta = abs( out.ci[0] - expected );
-	tol = 8.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. lower CI: '+out.ci[0]+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.ci[0], expected, 0 ), true, 'returns expected value' );
 
 	expected = equal.upper;
-	delta = abs( out.ci[1] - expected );
-	tol = 8.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. upper CI: '+out.ci[1]+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.ci[1], expected, 0 ), true, 'returns expected value' );
 
 	t.end();
 });
 
 tape( 'the function performs a two-sample t-test assuming the true difference in means being equal to the value of `difference` option', function test( t ) {
 	var expected;
-	var delta;
 	var out;
-	var tol;
 	var a;
 	var b;
 
@@ -271,23 +248,17 @@ tape( 'the function performs a two-sample t-test assuming the true difference in
 	t.strictEqual( out.statistic, diff.statistic, 'returns correct test statistic' );
 
 	expected = diff.lower;
-	delta = abs( out.ci[0] - expected );
-	tol = 6.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. lower CI: '+out.ci[0]+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.ci[0], expected, 0 ), true, 'returns expected value' );
 
 	expected = diff.upper;
-	delta = abs( out.ci[1] - expected );
-	tol = 12.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. a: ['+a+']. b: ['+b+']. upper CI: '+out.ci[1]+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.ci[1], expected, 0 ), true, 'returns expected value' );
 
 	t.end();
 });
 
 tape( 'the function performs a one-sided Welch two-sample t-test assuming unequal population variances', function test( t ) {
 	var expected;
-	var delta;
 	var out;
-	var tol;
 	var a;
 	var b;
 
@@ -299,21 +270,15 @@ tape( 'the function performs a one-sided Welch two-sample t-test assuming unequa
 
 	// Tested against R:
 	expected = less.pValue;
-	delta = abs( out.pValue - expected );
-	tol = 18.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. direction: less. a: ['+a+']. b: ['+b+']. pValue: '+out.pValue+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.pValue, expected, 17 ), true, 'returns expected value' );
 
 	expected = less.statistic;
-	delta = abs( out.statistic - expected );
-	tol = 2.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. direction: less. a: ['+a+']. b: ['+b+']. statistic: '+out.statistic+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.statistic, expected, 0 ), true, 'returns expected value' );
 
 	t.strictEqual( out.ci[0], NINF, 'returns -Infinity as lower bound of CI' );
 
 	expected = less.upper;
-	delta = abs( out.ci[1] - expected );
-	tol = 4.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. direction: less. a: ['+a+']. b: ['+b+']. upper CI: '+out.ci[1]+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.ci[1], expected, 0 ), true, 'returns expected value' );
 
 	out = ttest2( a, b, {
 		'alternative': 'greater'
@@ -321,19 +286,13 @@ tape( 'the function performs a one-sided Welch two-sample t-test assuming unequa
 
 	// Tested against R:
 	expected = greater.pValue;
-	delta = abs( out.pValue - expected );
-	tol = 4.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. direction: greater. a: ['+a+']. b: ['+b+']. pValue: '+out.pValue+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.pValue, expected, 0 ), true, 'returns expected value' );
 
 	expected = greater.statistic;
-	delta = abs( out.statistic - expected );
-	tol = 2.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. direction: greater. a: ['+a+']. b: ['+b+']. statistic: '+out.statistic+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.statistic, expected, 0 ), true, 'returns expected value' );
 
 	expected = greater.lower;
-	delta = abs( out.ci[0] - expected );
-	tol = 7.0 * EPS * abs( expected );
-	t.ok( delta <= tol, 'within tolerance. direction: greater. a: ['+a+']. b: ['+b+']. lower CI: '+out.ci[0]+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol );
+	t.strictEqual( isAlmostSameValue( out.ci[0], expected, 0 ), true, 'returns expected value' );
 
 	t.strictEqual( out.ci[1], PINF, 'returns Infinity as upper bound of CI' );