chore: changes from code review

Author: Neerajpathak07

lib/node_modules/@stdlib/stats/base/dnanmeanors/README.md

@@ -194,13 +194,13 @@ Computes the arithmetic mean of a double-precision floating-point strided array,
 const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
 
 double v = stdlib_strided_dnanmeanors( 6, x, 2 );
-// returns 4.6667
+// returns ~4.6667
 ```
 
 The function accepts the following arguments:
 
--   **N**:       `[in] CBLAS_INT` number of indexed elements.
--   **X**:       `[in] double*` input array.
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
 -   **strideX**: `[in] CBLAS_INT` stride length for `X`.
 
 ```c
@@ -215,13 +215,13 @@ Computes the arithmetic mean of a double-precision floating-point strided array,
 const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
 
 double v = stdlib_strided_dnanmeanors( 6, x, 2, 0 );
-// returns 4.6667
+// returns ~4.6667
 ```
 
 The function accepts the following arguments:
 
--   **N**:       `[in] CBLAS_INT` number of indexed elements.
--   **X**:       `[in] double*` input array.
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
 -   **strideX**: `[in] CBLAS_INT` stride length for `X`.
 -   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
 
@@ -253,7 +253,7 @@ double stdlib_strided_dnanmeanors_ndarray( const CBLAS_INT N, const double *X, c
 
 int main( void ) {
     // Create a strided array:
-    const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0,   7.0, 8.0, 0.0/0.0 };
+    const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
 
     // Specify the number of elements:
     const int N = 6;

lib/node_modules/@stdlib/stats/base/dnanmeanors/benchmark/benchmark.js

@@ -33,13 +33,13 @@ var dnanmeanors = require( './../lib/dnanmeanors.js' );
 // FUNCTIONS //
 
 /**
-* Returns a random value or `NaN`.
+* Returns a random number
 *
 * @private
-* @returns {number} random number or `NaN`
+* @returns {number} random number
 */
 function rand() {
-	if ( bernoulli( 0.8 < 1 ) ) {
+	if ( bernoulli( 0.5 < 1 ) ) {
 		return NaN;
 	}
 	return uniform( -10.0, 10.0 );

lib/node_modules/@stdlib/stats/base/dnanmeanors/benchmark/benchmark.native.js

@@ -42,13 +42,13 @@ var opts = {
 // FUNCTIONS //
 
 /**
-* Returns a random value or `NaN`.
+* Returns a random number
 *
 * @private
-* @returns {number} random number or `NaN`
+* @returns {number} random number
 */
 function rand() {
-	if ( bernoulli( 0.8 < 1 ) ) {
+	if ( bernoulli( 0.5 < 1 ) ) {
 		return NaN;
 	}
 	return uniform( -10.0, 10.0 );

lib/node_modules/@stdlib/stats/base/dnanmeanors/benchmark/benchmark.ndarray.js

@@ -33,13 +33,13 @@ var dnanmeanors = require( './../lib/ndarray.js' );
 // FUNCTIONS //
 
 /**
-* Returns a random value or `NaN`.
+* Returns a random number
 *
 * @private
-* @returns {number} random number or `NaN`
+* @returns {number} random number
 */
 function rand() {
-	if ( bernoulli( 0.8 < 1 ) ) {
+	if ( bernoulli( 0.5 < 1 ) ) {
 		return NaN;
 	}
 	return uniform( -10.0, 10.0 );

lib/node_modules/@stdlib/stats/base/dnanmeanors/benchmark/benchmark.ndarray.native.js

@@ -42,13 +42,13 @@ var opts = {
 // FUNCTIONS //
 
 /**
-* Returns a random value or `NaN`.
+* Returns a random number
 *
 * @private
-* @returns {number} random number or `NaN`
+* @returns {number} random number
 */
 function rand() {
-	if ( bernoulli( 0.8 < 1 ) ) {
+	if ( bernoulli( 0.5 < 1 ) ) {
 		return NaN;
 	}
 	return uniform( -10.0, 10.0 );

lib/node_modules/@stdlib/stats/base/dnanmeanors/benchmark/c/benchmark.length.c

@@ -102,7 +102,7 @@ static double benchmark1( int iterations, int len ) {
 	int i;
 
 	for ( i = 0; i < len; i++ ) {
-		if ( rand_double() < 0.2 ) {
+		if ( rand_double() < 0.5 ) {
 			x[ i ] = 0.0 / 0.0; // NaN
 		} else {
 			x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
@@ -140,7 +140,7 @@ static double benchmark2( int iterations, int len ) {
 	int i;
 
 	for ( i = 0; i < len; i++ ) {
-		if ( rand_double() < 0.2 ) {
+		if ( rand_double() < 0.5 ) {
 			x[ i ] = 0.0 / 0.0; // NaN
 		} else {
 			x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;