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2 cards from this section. Quick, good the night before a test.
Define big O notation.
Recall the concept of limits in mathematics.
What does it mean if t(n) is O(n²)?
Think about what 'growth rate' implies.
What does big O notation primarily measure?
Consider which aspect of computing this notation targets.
True or False: Omega notation represents an upper bound.
Think about the terms each notation represents.
Demonstrate that for f(n) = n² + n + 1, it is O(n²) by finding suitable constants.
Break down the function and see how n² dominates it.
Prove that n³ is not O(n²) by contradiction using definitions of big O.
Focus on the growth rates and their limits.
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