Final answer:
The time analysis, in big-O notation, of the evaluation method determines the algorithm's efficiency as the input size increases.
Step-by-step explanation:
The time analysis, in big-O notation, of the evaluation method can be determined by analyzing the algorithm's efficiency as the input size increases. Big-O notation represents the upper bound of the algorithm's time complexity. It provides an estimate of the worst-case scenario for the algorithm.
For example, if the evaluation method has a time complexity of O(n^2), it means that the time taken by the algorithm grows at a rate proportional to the square of the input size. This implies that as the input size increases, the time taken by the algorithm increases exponentially.
The time analysis allows us to understand the efficiency of the algorithm and make informed decisions regarding its use in different scenarios.