In layman terms it the running time of your algorithm.
The order of algorithms (growth) can be in Big-oh (O), little-oh(o), omega (Ω) or theta(Θ).
If you are having problems calculating RR please view some questions i asked before and vote if you understand.
Say you have a for loop:
for(i=1 to n)
x++
The order or time complexity of this piece of code is: O(n)
Why big-oh? Because we want the worst case at which this piece of code runs.
Read here (these define the complexity of an algorithm and informs you of how algorithms are done in polynomial time):
http://en.wikipedia.org/wiki/NP_(complexity)
http://en.wikipedia.org/wiki/NP-complete
http://en.wikipedia.org/wiki/NP-hard
Summary:
http://www.multiwingspan.co.uk/a23.php?page=types