fix: addressing first round comments

Author: Om-A-osc

lib/node_modules/@stdlib/stats/strided/dnanvarmpn/README.md

@@ -114,12 +114,12 @@ var v = dnanvarmpn( x.length, 1, 1.0/3.0, x, 1 );
 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).
+-   **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 and `n` corresponds to the number of non-`NaN` indexed elements. 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).
 -   **mean**: mean.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
 -   **strideX**: stride length for `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`,
+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 Float64Array = require( '@stdlib/array/float64' );
@@ -158,7 +158,7 @@ var Float64Array = require( '@stdlib/array/float64' );
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 
 var v = dnanvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 );
-// returns ~4.33333
+// returns ~4.3333
 ```
 
 The function has the following additional parameters:
@@ -187,7 +187,7 @@ var v = dnanvarmpn.ndarray( 5, 1, 1.25, x, 2, 1 );
 ## Notes
 
 -   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`.
+-   If `n - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements), both functions return `NaN`.
 
 </section>
 
@@ -263,8 +263,8 @@ double v = stdlib_strided_dnanvarmpn( 5, 1.0, 1.25, x, 2 );
 The function accepts the following arguments:
 
 -   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **correction**: `[in] double` 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 and `n` corresponds to the number of non-`NaN` indexed elements. 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).
 -   **mean**: `[in] double` mean.
--   **correction**: `[in] double` 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**: `[in] double*` input array.
 -   **strideX**: `[in] CBLAS_INT` stride length for `X`.
 
@@ -286,7 +286,7 @@ double v = stdlib_strided_dnanvarmpn_ndarray( 5, 1.0, 1.25, x, 2, 0 );
 The function accepts the following arguments:
 
 -   **N**: `[in] CBLAS_INT` number of indexed elements.
--   **correction**: `[in] double` 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).
+-   **correction**: `[in] double` 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 and `n` corresponds to the number of non-`NaN` indexed elements. 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).
 -   **mean**: `[in] double` mean.
 -   **X**: `[in] double*` input array.
 -   **strideX**: `[in] CBLAS_INT` stride length for `X`.

lib/node_modules/@stdlib/stats/strided/dnanvarmpn/docs/repl.txt

@@ -20,8 +20,9 @@
     correction: number
         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 according to `N - c` where `c` corresponds to the
-        provided degrees of freedom adjustment. When computing the variance of a
+        of the variance according to `n - c` where `c` corresponds to the
+        provided degrees of freedom adjustment and `n` corresponds to the
+        number of non-`NaN` indexed elements. When computing the 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, setting this parameter to
@@ -79,8 +80,9 @@
     correction: number
         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 according to `N - c` where `c` corresponds to the
-        provided degrees of freedom adjustment. When computing the variance of a
+        of the variance according to `n - c` where `c` corresponds to the
+        provided degrees of freedom adjustment and `n` corresponds to the
+        number of non-`NaN` indexed elements. When computing the 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, setting this parameter to