'Ο' is used for an estimate in excess (it's supposed to be a capital omicron, not an 'oh')
'Ω' is used for an estimate in defect (o-mega "is bigger" than o-micron)
'Θ' is used for the actual growth.
For example: mergesort is Ω(1), Ο(n2), Θ(n log n)
This is important since it's quite common to know boundaries on the complexity, but not the exact complexity. For example, matrix multiplication is Ω(n2) (you have to generate all the elements), and surely Ο(n3) (there is a naif algorithm with that complexity), but we don't know the exact function.
-- dakkar - Mobilis in mobile