To determine the time complexity of insertion sort, we need to analyze its algorithm.

1. First, let's consider the best-case scenario. In the best case, the input array is already sorted. In this case, insertion sort has a time complexity of O(n), where n is the number of elements in the array. This is because each element only needs to be compared with the previous element once, and no shifting of elements is required.

2. Next, let's consider the worst-case scenario. In the worst case, the input array is sorted in reverse order. In this case, insertion sort has a time complexity of O(n^2). This is because for each element, it needs to be compared with all the previous elements and potentially shifted to its correct position.

3. Finally, let's consider the average-case scenario. In the average case, the input array is randomly ordered. In this case, insertion sort also has a time complexity of O(n^2). This is because, on average, each element needs to be compared with half of the previous elements and potentially shifted.

In summary, the time complexity of insertion sort is O(n^2) in the worst case and average case, and O(n) in the best case.

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To determine the time complexity of insertion sort, we need to analyze its algorithm.

1. First, let's consider the best-case scenario. In the best case, the input array is already sorted. In this case, insertion sort has a time complexity of O(n), where n is the number of elements in the array. This is because each element only needs to be compared with the previous element once, and no shifting of elements is required.

2. Next, let's consider the worst-case scenario. In the worst case, the input array is sorted in reverse order. In this case, insertion sort has a time complexity of O(n^2). This is because for each element, it needs to be compared with all the previous elements and potentially shifted to its correct position.

3. Finally, let's consider the average-case scenario. In the average case, the input array is randomly ordered. In this case, insertion sort also has a time complexity of O(n^2). This is because, on average, each element needs to be compared with half of the previous elements and potentially shifted.

In summary, the time complexity of insertion sort is O(n^2) in the worst case and average case, and O(n) in the best case.

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To determine the time complexity of insertion sort, we need to analyze its algorithm.

1. First, let's consider the best-case scenario. In the best case, the input array is already sorted. In this case, insertion sort has a time complexity of O(n), where n is the number of elements in the array. This is because each element only needs to be compared with the previous element once, and no shifting of elements is required.

2. Next, let's consider the worst-case scenario. In the worst case, the input array is sorted in reverse order. In this case, insertion sort has a time complexity of O(n^2). This is because for each element, it needs to be compared with all the previous elements and potentially shifted to its correct position.

3. Finally, let's consider the average-case scenario. In the average case, the input array is randomly ordered. In this case, insertion sort also has a time complexity of O(n^2). This is because, on average, each element needs to be compared with half of the previous elements and potentially shifted.

In summary, the time complexity of insertion sort is O(n^2) in the worst case and average case, and O(n) in the best case.

Question2Max. score: 3.00What is the time complexity of insertion sort?

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