fix: fixed repl documentation

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---

Author: sagar7162

lib/node_modules/@stdlib/stats/base/ndarray/svariance/docs/repl.txt

@@ -3,11 +3,27 @@
     Computes the variance of a one-dimensional single-precision
     floating-point ndarray.
 
+    If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+    If `N - c` is less than or equal to `0` (where `N` corresponds to the number
+    of elements in the input ndarray and `c` corresponds to the provided degrees
+    of freedom adjustment), the function returns `NaN`.
+
     Parameters
     ----------
-    arrays: Array<ndarray>
-        Array-like object containing a one-dimensional input ndarray and a
-        zero-dimensional ndarray specifying a degrees of freedom adjustment.
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing two elements: a one-dimensional input
+        ndarray and a zero-dimensional ndarray specifying the degrees of freedom
+        adjustment. Providing a non-zero degrees of freedom adjustment has the
+        effect of adjusting the divisor during the calculation of the variance
+        according to `N-c` where `N` is the number of elements in the input
+        ndarray and `c` corresponds to the provided degrees of freedom
+        adjustment. 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 `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).
 
     Returns
     -------
@@ -16,22 +32,22 @@
 
     Examples
     --------
-    // Standard Usage:
-    > var Float32Array = require( '@stdlib/array/float32' );
-    > var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
-    > var ndarray = require( '@stdlib/ndarray/base/ctor' );
-    > var xbuf = new Float32Array( [ 1.0, -2.0, 2.0 ] );
-    > var x = new ndarray( 'float32', xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
-    > var correction = scalar2ndarray( 1.0, { 'dtype': 'float32' } );
-    > {{alias}}( [ x, correction ] )
-    ~4.333333
+    // Create input ndarray:
+    > var xbuf = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] );
+    > var dt = 'float32';
+    > var sh = [ xbuf.length ];
+    > var st = [ 1 ];
+    > var oo = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord );
+
+    // Create correction ndarray:
+    > var opts = { 'dtype': dt };
+    > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
 
-    // Using ndarray properties:
-    > xbuf = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-    > x = new ndarray( 'float32', xbuf, [ 4 ], [ 2 ], 1, 'row-major' );
-    > correction = scalar2ndarray( 1.0, { 'dtype': 'float32' } );
+    // Compute the variance:
     > {{alias}}( [ x, correction ] )
-    6.25
+    ~4.333333
 
     See Also
     --------