Replace then with them

spotted typo.

concepts/lists/about.md

@@ -1,6 +1,6 @@
 In Python, a [list][list] is a mutable collection of items in _sequence_. Like most collections (_see the built-ins [`tuple`][tuple], [`dict`][dict] and [`set`][set]_), lists can hold reference to any (or multiple) data type(s) - including other lists. Like any [sequence][sequence type], items are referenced by 0-based index number, and can be copied in whole or in part via _slice notation_. Lists support all [common sequence operations][common sequence operations], as well as [mutable sequence operations][mutable sequence operations] like `.append()` and `.reverse()`. They can be iterated over in a loop by using the `for item in` construct.
 
-Under the hood, lists are implemented as [dynamic arrays][dynamic array] -- similar to Java's [`Arraylist`][arraylist] type. Lists are most often used to store groups of similar data (_strings, numbers, sets etc._) of unknown length (_the number of entries may arbitrarily expand or shrink_). Accessing items in a list, checking for membership via `in`, or appending items to the "right-hand" side of a list are all very efficient. Appending to the "left-hand" side or inserting into the middle of a list is much _less_ efficient because it requires shifting items to keep then in sequence.
+Under the hood, lists are implemented as [dynamic arrays][dynamic array] -- similar to Java's [`Arraylist`][arraylist] type. Lists are most often used to store groups of similar data (_strings, numbers, sets etc._) of unknown length (_the number of entries may arbitrarily expand or shrink_). Accessing items in a list, checking for membership via `in`, or appending items to the "right-hand" side of a list are all very efficient. Appending to the "left-hand" side or inserting into the middle of a list is much _less_ efficient because it requires shifting items to keep them in sequence.
 
 Because lists are mutable and can contain references to arbitrary objects, they take up more memory space than a fixed-size `array.array` type of the same apparent length. Despite this, lists are an extremely flexible and useful data structure and many built-in methods and operations in Python produce lists as their output.