Understanding the following standard sorting algorithms

• What is the purpose of sorting algorithms?

  To arrange data
• Sorting algorithms are methods for arranging data in a specific order
• How does Merge Sort divide the dataset?

  In half
• Merge Sort is generally more efficient than Bubble Sort due to its better time complexity.


  True
• Merge Sort has a time complexity of O(n log n), making it more efficient than Bubble Sort.


  True
• Steps of Bubble Sort

  1️⃣ Compare the first two elements

  2️⃣ If the first is greater, swap them

  3️⃣ Move to the next pair

  4️⃣ Repeat until the dataset is sorted
• Bubble Sort has a time complexity of O(n^2), making it inefficient for large datasets.


  True
• What is a sorting algorithm used for?

  Arranging data in order
• Bubble Sort has a time complexity of O(n^2).


  True
• Merge Sort divides the dataset in half
• Why is Bubble Sort inefficient for large datasets?

  Its time complexity is O(n^2)
• Insertion Sort has a time complexity of O(n^2).


  True
• What action is performed on the sorted elements in Insertion Sort to create space for the next element?

  Shifting up
• Insertion Sort is more efficient than Bubble Sort for small datasets.
• Selection Sort works by repeatedly finding the minimum element in the unsorted part of the dataset.


  True
• What is the time complexity of Selection Sort?

  O(n^2)
• Merge Sort is generally more efficient than Bubble Sort for large datasets.
• What are sorting algorithms used for?

  Arranging data
• What is the time complexity of Bubble Sort?

  O(n^2)
• What is the time complexity of Merge Sort?

  O(n log n)
• How does Insertion Sort work?

  Inserts elements iteratively
• Selection Sort selects the smallest element and moves it to the beginning
• What is the first step in Bubble Sort?

  Compare the first two elements
• How does Insertion Sort handle unsorted elements?

  Inserts them into sorted portion
• Selection Sort repeatedly finds the minimum element in the unsorted portion.
• What is the time complexity of Selection Sort?

  O(n^2)
• Selection Sort repeats the process of finding the minimum and swapping until the entire dataset is sorted.

  True
• Merge Sort has a time complexity of O(n log n)
• What is the first step in Quick Sort?

  Select a pivot
• Quick Sort uses recursion to sort the left and right partitions after partitioning around the pivot.

  True
• Merge Sort requires additional space of O(n)
• Bubble Sort has a time complexity of O(n^2), making it inefficient for large datasets.


  True
• Merge Sort has a time complexity of O(n log n), making it more efficient than Bubble Sort for large datasets.
• Match the sorting algorithm with its time complexity:

  Bubble Sort ↔️ O(n^2)

  Merge Sort ↔️ O(n log n)
• What is the key operation of Bubble Sort?

  Swapping adjacent elements
• In Bubble Sort, if the first element is greater than the second, they are swapped
• Why is Bubble Sort inefficient for large datasets?

  It requires multiple passes
• What is the time complexity of Merge Sort?

  O(n log n)
• Bubble Sort repeatedly swaps adjacent elements if they are in the wrong order
• What is the time complexity of Merge Sort?

  O(n log n)