diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/README.md b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/README.md
index bd18036609bb..aaa18533aeac 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/README.md
@@ -102,15 +102,75 @@ var y = dist.logpdf( 0.8 );
 
 ## Examples
 
-<!-- TODO: better examples -->
-
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var objectKeys = require( '@stdlib/utils/keys' );
 var kumaraswamy = require( '@stdlib/stats/base/dists/kumaraswamy' );
 
-console.log( objectKeys( kumaraswamy ) );
+// Create a Kumaraswamy distribution object:
+var a = 2.0;
+var b = 5.0;
+var dist = new kumaraswamy.Kumaraswamy( a, b );
+
+// Calculate basic distribution properties:
+console.log( 'Mean: %d', dist.mean );
+console.log( 'Median: %d', dist.median );
+console.log( 'Mode: %d', dist.mode );
+console.log( 'Variance: %d', dist.variance );
+
+// Evaluate the probability density function (PDF):
+var x = 0.5;
+var y = dist.pdf( x );
+console.log( 'PDF at x = %d: %d', x, y );
+
+// Evaluate the cumulative distribution function (CDF):
+y = dist.cdf( x );
+console.log( 'CDF at x = %d: %d', x, y );
+
+// Evaluate the natural logarithm of PDF and CDF:
+console.log( 'Log PDF at x = %d: %d', x, dist.logpdf( x ) );
+console.log( 'Log CDF at x = %d: %d', x, dist.logcdf( x ) );
+
+// Calculate the quantile for a given probability:
+var p = 0.75;
+x = dist.quantile( p );
+console.log( 'Quantile at p = %d: %d', p, x );
+
+// Use standalone distribution functions:
+x = 0.3;
+y = kumaraswamy.pdf( x, a, b );
+console.log( 'Standalone PDF at x = %d: %d', x, y );
+
+y = kumaraswamy.cdf( x, a, b );
+console.log( 'Standalone CDF at x = %d: %d', x, y );
+
+y = kumaraswamy.quantile( 0.9, a, b );
+console.log( 'Standalone Quantile at p = 0.9: %d', y );
+
+// Calculate additional distribution properties:
+console.log( 'Kurtosis: %d', kumaraswamy.kurtosis( a, b ) );
+console.log( 'Skewness: %d', kumaraswamy.skewness( a, b ) );
+console.log( 'Standard Deviation: %d', kumaraswamy.stdev( a, b ) );
+
+// Demonstrate the effect of different shape parameters:
+console.log( '\nEffect of shape parameters:' );
+var shapes = [
+    [ 0.5, 0.5 ],
+    [ 5.0, 1.0 ],
+    [ 1.0, 5.0 ],
+    [ 2.0, 2.0 ],
+    [ 10.0, 10.0 ]
+];
+var params;
+var i;
+for ( i = 0; i < shapes.length; i++ ) {
+    params = shapes[i];
+    console.log( '\na = %d, b = %d', params[0], params[1] );
+    console.log( 'Mean: %d', kumaraswamy.mean( params[0], params[1] ) );
+    console.log( 'Median: %d', kumaraswamy.median( params[0], params[1] ) );
+    console.log( 'Mode: %d', kumaraswamy.mode( params[0], params[1] ) );
+    console.log( 'Skewness: %d', kumaraswamy.skewness( params[0], params[1] ) );
+}
 ```
 
 </section>
diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/examples/index.js
index 668493a128a3..1f0b34c120c5 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/examples/index.js
@@ -18,7 +18,69 @@
 
 'use strict';
 
-var objectKeys = require( '@stdlib/utils/keys' );
 var kumaraswamy = require( './../lib' );
 
-console.log( objectKeys( kumaraswamy ) );
+// Create a Kumaraswamy distribution object:
+var a = 2.0;
+var b = 5.0;
+var dist = new kumaraswamy.Kumaraswamy( a, b );
+
+// Calculate basic distribution properties:
+console.log( 'Mean: %d', dist.mean );
+console.log( 'Median: %d', dist.median );
+console.log( 'Mode: %d', dist.mode );
+console.log( 'Variance: %d', dist.variance );
+
+// Evaluate the probability density function (PDF):
+var x = 0.5;
+var y = dist.pdf( x );
+console.log( 'PDF at x = %d: %d', x, y );
+
+// Evaluate the cumulative distribution function (CDF):
+y = dist.cdf( x );
+console.log( 'CDF at x = %d: %d', x, y );
+
+// Evaluate the natural logarithm of PDF and CDF:
+console.log( 'Log PDF at x = %d: %d', x, dist.logpdf( x ) );
+console.log( 'Log CDF at x = %d: %d', x, dist.logcdf( x ) );
+
+// Calculate the quantile for a given probability:
+var p = 0.75;
+x = dist.quantile( p );
+console.log( 'Quantile at p = %d: %d', p, x );
+
+// Use standalone distribution functions:
+x = 0.3;
+y = kumaraswamy.pdf( x, a, b );
+console.log( 'Standalone PDF at x = %d: %d', x, y );
+
+y = kumaraswamy.cdf( x, a, b );
+console.log( 'Standalone CDF at x = %d: %d', x, y );
+
+y = kumaraswamy.quantile( 0.9, a, b );
+console.log( 'Standalone Quantile at p = 0.9: %d', y );
+
+// Calculate additional distribution properties:
+console.log( 'Kurtosis: %d', kumaraswamy.kurtosis( a, b ) );
+console.log( 'Skewness: %d', kumaraswamy.skewness( a, b ) );
+console.log( 'Standard Deviation: %d', kumaraswamy.stdev( a, b ) );
+
+// Demonstrate the effect of different shape parameters:
+console.log( '\nEffect of shape parameters:' );
+var shapes = [
+	[ 0.5, 0.5 ],
+	[ 5.0, 1.0 ],
+	[ 1.0, 5.0 ],
+	[ 2.0, 2.0 ],
+	[ 10.0, 10.0 ]
+];
+var params;
+var i;
+for ( i = 0; i < shapes.length; i++ ) {
+	params = shapes[ i ];
+	console.log( '\na = %d, b = %d', params[0], params[1] );
+	console.log( 'Mean: %d', kumaraswamy.mean( params[0], params[1] ) );
+	console.log( 'Median: %d', kumaraswamy.median( params[0], params[1] ) );
+	console.log( 'Mode: %d', kumaraswamy.mode( params[0], params[1] ) );
+	console.log( 'Skewness: %d', kumaraswamy.skewness( params[0], params[1] ) );
+}