The time complexity for finding an element in a binary search tree is 0(logn) 0(

Question

The time complexity for finding an element in a binary search tree is 0(logn) 0(nlogn) 0(1) 0(n) The time complexity for inserting an element in a list is 0(logn). true false Suppose you want to store students and perform the operations to insert and delete students. Which data structure is best for this application? A stack an array list A linked list A queue the of a node is the length of the path from the root to the node. length height degree depth the is to visit the current node first, then the left subtree of the current node, and finally the right subtree of the current node. post order traversal preorder traversal in order traversal breadth-first traversal True or False? You can traverse the elements in a BST using a for-each loop. False True Show the preorder after inserting 1, 2, 4, 6, 3 into an empty binary search tree. 2 4 1 3 6 1 4 2 3 6 1 2 6 4 3 1 2 4 3 6 1 2 3 4 6 The time complexity for finding an element in a binary search tree is 0(1) 0(n) 0(logn) 0(n logn)

Explanation / Answer

73) In a perfectly balanced tree, you can see that you get 2n-1 nodes for every n levels. That means for 15 nodes, you never have to search more than four nodes to find it so A is the answer.

74) B because complexity of inserting number in list is O(n)

75) C the linked list

76) D depth of node

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