adamki/gist:3007a72b4ec0f8291905

## gistfile1.txt
**Step One**: Watch [Sorting Algorithms in JavaScript](https://www.youtube.com/watch?v=uRyqlhjXYQI)

**Step Two**: Fork this gist.

**Step Three**: Respond to this question in your fork: "What are some of the balances and trade offs between different sorting algoritms?"

Trying NOT to oversimplify this questions, but it is a balnace of Space and Time. Space refers to memory. Time refers to the amount time time consumed while performing a task.

Jenn describes how Big O is a variable that can be used to measure run time. While handy, this doesn't take into account when SPACE must be taken into consideration. We can use the example of a Space efficient sort (Bubble) contrasted with a time effecient sort(merge). Depending on the use case, and resources, one may choose a slightly slower sort to save space.


**Step Four**: _Totally Optional_: take a look at some of the other forks and comment if the spirit moves you.
	Step One: Watch [Sorting Algorithms in JavaScript](https://www.youtube.com/watch?v=uRyqlhjXYQI)

	Step Two: Fork this gist.

	Step Three: Respond to this question in your fork: "What are some of the balances and trade offs between different sorting algoritms?"

	Trying NOT to oversimplify this questions, but it is a balnace of Space and Time. Space refers to memory. Time refers to the amount time time consumed while performing a task.

	Jenn describes how Big O is a variable that can be used to measure run time. While handy, this doesn't take into account when SPACE must be taken into consideration. We can use the example of a Space efficient sort (Bubble) contrasted with a time effecient sort(merge). Depending on the use case, and resources, one may choose a slightly slower sort to save space.



	Step Four: _Totally Optional_: take a look at some of the other forks and comment if the spirit moves you.