Question

Question
Which of the following Big O notations is appropriate for the complexity of a sort algorithm?(1 point)
Responses

O(1)
upper O left parenthesis 1 right parenthesis

O(log n)
upper O left parenthesis log n right parenthesis

O(n)
upper O left parenthesis n right parenthesis

O(n^2)

Answer 1

The appropriate Big O notation for the complexity of a sorting algorithm depends on the specific algorithm being used. Here are common complexities for various sorting algorithms:

1. **O(1)**: This notation indicates constant time complexity, which is not applicable for sorting.

2. **O(log n)**: This notation indicates logarithmic time complexity, which does not apply to sorting algorithms.

3. **O(n)**: This indicates linear time complexity, which applies to certain specialized sorting algorithms like Counting Sort or Radix Sort under specific conditions but does not apply to comparison-based sorts.

4. **O(n^2)**: This indicates quadratic time complexity, which is typical for comparison-based sorting algorithms like Bubble Sort, Insertion Sort, and Selection Sort in the average and worst cases.

Thus, while **O(n^2)** can be appropriate for several common sorting algorithms, the most suitable Big O notation for sorting in general depends on the algorithm. For comparison-based sorts, O(n log n) is often the best average case complexity, but is not listed in your options. Among the given choices, **O(n^2)** is the most representative of common sorting algorithms.