Quick Sort has the best average time complexity of O(n log n), making it more efficient than the other options listed.

Quick Sort has the best average-case performance among the listed algorithms with O(n log n).

Merge Sort has an average-case time complexity of O(n log n), which is better than the average-case complexities of the other options.

Merge Sort is based on the divide and conquer strategy.

Merge Sort is based on the divide and conquer technique.

Merge Sort is a sorting algorithm that uses the divide-and-conquer paradigm to sort elements.

Merge Sort is a stable sorting algorithm that uses the divide-and-conquer principle.

Merge Sort is based on the divide-and-conquer principle, where the array is divided into halves, sorted, and then merged.

Merge Sort is best suited for large datasets that do not fit into memory due to its external sorting capabilities.

Merge sort is best suited for linked lists as it can be implemented without additional space and works well with the linked structure.

Insertion Sort is best suited for partially sorted data as it can take advantage of the existing order.

Quick Sort is generally considered the most efficient for large datasets due to its average-case time complexity of O(n log n).

Quick Sort is generally considered the fastest for large datasets due to its average time complexity of O(n log n).

Quick Sort is generally considered the most efficient for large datasets due to its average time complexity of O(n log n).

Insertion Sort is generally faster for small datasets due to its low overhead and simplicity.

Quick Sort is generally the fastest for large datasets due to its average-case time complexity of O(n log n).

Merge Sort is not an in-place sorting algorithm as it requires additional space for merging.

Quick Sort is not a stable sorting algorithm, as it can change the relative order of equal elements.

Quick sort is often used in real-world applications for its efficiency, especially with large datasets.

Merge Sort is a stable sorting algorithm, meaning it maintains the relative order of equal elements.

Merge Sort is a stable sorting algorithm, meaning it maintains the relative order of equal elements.

Insertion Sort is generally faster for small datasets due to its low overhead and simplicity.

Merge Sort is often used in the 'sort' function due to its stable sorting and O(n log n) time complexity.

Heap Sort uses a binary heap data structure.

Tree Sort uses a binary tree structure to sort elements by inserting them into a binary search tree.

Merge Sort uses a divide-and-conquer approach by dividing the array into halves, sorting them, and then merging.

Merge Sort uses a divide-and-conquer strategy to sort the array.

Logistic Regression is a common algorithm used for binary classification tasks, predicting the probability of a binary outcome.

Imputation is a technique used to fill in missing values in a dataset.

To handle multicollinearity, one can increase the sample size, remove one of the correlated variables, or use more complex models like Ridge regression.