What is the time complexity of Absolute Difference Between Maximum and Minimum K Elements?

The optimal solution for Absolute Difference Between Maximum and Minimum K Elements runs in O(n log n) time and uses O(1) space. Sorting the array dominates the time complexity, making it O(n log n).

What is the brute force solution for Absolute Difference Between Maximum and Minimum K Elements?

The brute force approach for Absolute Difference Between Maximum and Minimum K Elements is Brute Force, with O(n²) time complexity and O(1) space complexity. We can find the k largest and k smallest elements by checking all combinations, but this is inefficient. Sorting the array simplifies the task. The optimal Optimal Solution approach improves this to O(n log n).

What algorithm or data structure is used to solve Absolute Difference Between Maximum and Minimum K Elements?

Absolute Difference Between Maximum and Minimum K Elements uses the following concepts: Array, Sorting. The recommended patterns to study are: Sorting, Array.

What are the interview tips for Absolute Difference Between Maximum and Minimum K Elements?

Explain your thought process clearly. Consider edge cases like duplicates or all elements being the same. Practice coding the solution without looking at notes.

What are common mistakes when solving Absolute Difference Between Maximum and Minimum K Elements?

Not sorting the array before accessing elements. Confusing indices when summing elements.

#3774

Absolute Difference Between Maximum and Minimum K Elements

Easy

ArraySortingSortingArray

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Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n log n)
Space	O(1)	O(1)

💡

Intuition

Time O(n log n)Space O(1)

Sorting the array allows us to easily access the k largest and k smallest elements directly, making the solution efficient.

⚙️

Algorithm

3 steps

1Step 1: Sort the array in ascending order.
2Step 2: Sum the first k elements for the smallest sum.
3Step 3: Sum the last k elements for the largest sum and return their absolute difference.

solution.py3 lines

1def max_min_difference(nums, k):
2    nums.sort()
3    return abs(sum(nums[-k:]) - sum(nums[:k]))

ℹ

Complexity note: Sorting the array dominates the time complexity, making it O(n log n).

1Sorting simplifies finding k largest and smallest elements.
2Absolute difference can be computed directly from sums.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.