BST Practice Question

Duration: 2 min

This video lesson is available to enrolled students.

Return to /learn/COCUBES-PREPARATION/data-structures/tree/bst-basics-operations/asset-bst-practice-question after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. Quantitative Aptitude: Number System, Divisibility Rules, HCF LCM, Percentage, Ratio and Proportion (Ratios), Average, Profit and Loss, Simple Interest and Compound Interest, Mixture and Alligation, Partnership, Age Problems, Time and Work, Pipe and Cistern, Speed Time and Distance, Algebra, Arithmetic, Data Interpretation, Sequence and Series (Series), Logarithm, Powers and Exponents (Surds and Indices), Permutation and Combination, Probability, Speed Mathematics and Basic Mathematics, Trigonometry
  2. Logical Reasoning: Coding Decoding, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Seating Arrangements, Puzzle Solving (Puzzles), Data Arrangement, Syllogisms, Inequality, Data Sufficiency, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Series (Number and Letter Series) (Numerical Relations and Reasoning), Venn Diagram, Logical Sequence Of Words, Calendar, Clock, Cubes & Dices, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning)
  3. Verbal Ability: Noun, Pronoun, Adjectives, Verb, Adverb, Tenses, Subject Verb Agreement (Verb Noun Agreement), Articles, Preposition, Conjunction, Modals, Determiner, Vocabulary, Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Cloze Test (Cloze Passage), Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Active Passive Voice (Voice), Direct and Indirect Speech, Sentence Construction
  4. Data Structures (Domain Test): Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  5. Algorithms (Domain Test): Algorithm Analysis, Sorting Algorithms, Time Complexity Analysis, Greedy Algorithms
  6. OOPs (Domain Test): Object Oriented Programming (OOPS)
  7. DBMS (Domain Test): Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, Relational Calculus, Transaction Management, Concurrency Control, Database Recovery, ORDBMS, Database Security & Authorization, Query Processing & Optimization, Enhanced Data Models, Data Warehousing & Mining, Big Data Systems, NoSQL
  8. SQL (Domain Test): SQL
  9. Operating Systems (Domain Test): Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Windows OS, Linux OS, Security, Distributed Systems, Virtual Machines
  10. Computer Networks (Domain Test): Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security, Mobile Technology, Cloud Computing and IoT, Cyber and Info Security
  11. Coding: Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Java, Python for Placements by Yash Sir
  12. Written English Test: English Writing Ability
  13. Psychometric Test: Behavioral Assessment (Behavioral Competency Profiling) (Psychometric Test)
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This lecture segment addresses a problem involving the calculation of the expected number of comparisons for a random search operation within a Binary Search Tree (BST). The instructor presents a specific tree structure and asks students to determine the average search cost. The solution involves identifying the depth of every node, summing these depths to find the total comparisons required for all keys, and then dividing by the total number of nodes to find the mean. The final result is matched against multiple-choice options to identify the correct answer.

Chapters

  1. 0:00 – 1:48 00:00-01:48

    The video opens with the problem statement 'Consider the following Binary Search Tree' alongside a diagram. The tree has root 10, left child 5, right child 20. Node 5 has left child 4. Node 20 has left child 15 and right child 30. Node 4 has a right child 11. The question text appears: 'If we randomly search one of the keys present in above BST, what would be the expected number of comparisons?' Options (A) 2.75, (B) 2.25, (C) 2.57 are visible. The instructor begins solving by annotating the tree with comparison counts. He marks '1' next to 10, '2' next to 5 and 20, '3' next to 4, 15, and 30, and '4' next to 11. He formulates the summation equation on the right side of the screen: 1 + 2 + 2 + 3 + 3 + 3 + 4. He underlines the sum. He divides the sum by 7, writing the fraction 18/7. He performs long division to get 2.57 and circles option (C).

The video effectively teaches how to compute the average search cost in a BST. By assigning a cost equal to the node's depth plus one and averaging these costs across all nodes, the expected number of comparisons is derived. This method highlights that unbalanced trees can have higher average search costs compared to balanced ones.

Loading lesson…