fix: correct variancepn README

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Author: gururaj1512

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

@@ -2,7 +2,7 @@
 
 @license Apache-2.0
 
-Copyright (c) 2025 The Stdlib Authors.
+Copyright (c) 2020 The Stdlib Authors.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -98,15 +98,14 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note,
 var variancepn = require( '@stdlib/stats/base/variancepn' );
 ```
 
-#### variancepn( N, correction, x, stride )
+#### variancepn( N, correction, x, strideX )
 
-Computes the [variance][variance] of a strided array `x` using a two-pass algorithm.
+Computes the [variance][variance] of a strided array using a two-pass algorithm.
 
 ```javascript
 var x = [ 1.0, -2.0, 2.0 ];
-var N = x.length;
 
-var v = variancepn( N, 1, x, 1 );
+var v = variancepn( x.length, 1, x, 1 );
 // returns ~4.3333
 ```
 
@@ -115,17 +114,14 @@ The function has the following parameters:
 -   **N**: number of indexed elements.
 -   **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
 -   **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`,
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
 var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
-var N = floor( x.length / 2 );
 
-var v = variancepn( N, 1, x, 2 );
+var v = variancepn( 4, 1, x, 2 );
 // returns 6.25
 ```
 
@@ -135,42 +131,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = variancepn( N, 1, x1, 2 );
+var v = variancepn( 4, 1, x1, 2 );
 // returns 6.25
 ```
 
-#### variancepn.ndarray( N, correction, x, stride, offset )
+#### variancepn.ndarray( N, correction, x, strideX, offsetX )
 
 Computes the [variance][variance] of a strided array using a two-pass algorithm and alternative indexing semantics.
 
 ```javascript
 var x = [ 1.0, -2.0, 2.0 ];
-var N = x.length;
 
-var v = variancepn.ndarray( N, 1, x, 1, 0 );
+var v = variancepn.ndarray( x.length, 1, x, 1, 0 );
 // returns ~4.33333
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
 var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
-var N = floor( x.length / 2 );
 
-var v = variancepn.ndarray( N, 1, x, 2, 1 );
+var v = variancepn.ndarray( 4, 1, x, 2, 1 );
 // returns 6.25
 ```
 
@@ -184,6 +173,7 @@ var v = variancepn.ndarray( N, 1, x, 2, 1 );
 
 -   If `N <= 0`, both functions return `NaN`.
 -   If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), both functions return `NaN`.
+-   Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).
 -   Depending on the environment, the typed versions ([`dvariancepn`][@stdlib/stats/strided/dvariancepn], [`svariancepn`][@stdlib/stats/strided/svariancepn], etc.) are likely to be significantly more performant.
 
 </section>
@@ -259,6 +249,8 @@ console.log( v );
 
 [@schubert:2018a]: https://doi.org/10.1145/3221269.3223036
 
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
 <!-- <related-links> -->
 
 [@stdlib/stats/strided/dvariancepn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dvariancepn