Corrected capitalization, corrected to American spellings and typos (#30685)

* Translate challenge subtitles and example challenge text to Spanish

* Corrected errors in syntax and punctuation

* Multiple corrections of it/s to its plus other grammar corrections

* Correction and added paragraph to CSS Flex article

* Corrected my own typo

* Corrected capitalization, American spellings and typos

guide/english/algorithms/binary-search-trees/index.md

@@ -17,7 +17,7 @@ A binary search tree (BST) adds these two characteristics:
 The BST is built up on the idea of the <a href='https://guide.freecodecamp.org/algorithms/search-algorithms/binary-search' targer='_blank' rel='nofollow'>binary search</a> algorithm, which allows for fast lookup, insertion and removal of nodes. The way that they are set up means that, on average, each comparison allows the operations to skip about half of the tree, so that each lookup, insertion or deletion takes time proportional to the logarithm of the number of items stored in the tree, `O(log n)`. However, some times the worst case can happen, when the tree isn't balanced and the time complexity is `O(n)` for all three of these functions. That is why self-balancing trees (AVL, red-black, etc.) are a lot more effective than the basic BST.
 
 
-**Worst case scenario example:** This can happen when you keep adding nodes that are *always* larger than the node before (it's parent), the same can happen when you always add nodes with values lower than their parents.
+**Worst case scenario example:** This can happen when you keep adding nodes that are *always* larger than the node before (its parent), the same can happen when you always add nodes with values lower than their parents.
 
 ### Basic operations on a BST
 - Create: creates an empty tree.

guide/english/algorithms/sorting-algorithms/index.md

@@ -46,7 +46,7 @@ Sorting algorithms are said to be `in place` if they require a constant `O(1)` e
 
 * `Insertion sort` and `Quick-sort` are `in place` sort as we move the elements about the pivot and do not actually use a separate array which is NOT the case in merge sort where the size of the input must be allocated beforehand to store the output during the sort.
 
-* `Merge Sort` is an example of `out place` sort as it require extra memory space for it's operations.
+* `Merge Sort` is an example of `out place` sort as it require extra memory space for its operations.
 
 ### Best possible time complexity for any comparison based sorting
 Any comparison based sorting algorithm must make at least nLog2n comparisons to sort the input array, and Heapsort and merge sort are asymptotically optimal comparison sorts.This can be easily proved by drawing the desicion tree diagram.