Max, Min Degree

Duration: 4 min

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Inside: a video lesson and guided study material.

Module outline

  1. Discrete Mathematics: Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic
  2. DataBase Management System/DBMS: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Relational Calculus, Transaction Management, Concurrency Control
  3. Digital Electronics: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  4. Computer Architecture: Floating Point Rep, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design
  5. Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management
  6. C Language: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  7. Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  8. Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos
  9. Computer Networks: Introduction to CN, 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
  10. Theory Of Computation/Automata Theory: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines, Complexity Theory
  11. Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment
  12. Engineering Mathematics: Permutation and Combination, Linear Algebra, Calculus, Probability, Statistics
  13. General Aptitude: Ratio and Proportion (Ratios), Divisibility Rules, Data Interpretation, Logarithm, Number System, HCF LCM, Sequence and Series (Series), Speed Time and Distance, Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Data Sufficiency, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Percentage, Mensuration and Geometry, Mental Ability, Arithmetic, Profit and Loss, Powers and Exponents (Surds and Indices), Average, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Syllogisms, Venn Diagram, Seating Arrangements, Blood Relations, Directions (Direction Test), Analogy, Algebra, Time and Work, Analytical Reasoning (Counting Figures Reasoning), Puzzle Solving (Puzzles), Cubes & Dices, Ranking, Order and Sequence, Mixture and Alligation, Age Problems, Clock, Selection Decision Table (Decision Making), Data Arrangement
  14. English (Verbal Aptitude): Vocabulary, Noun, Subject Verb Agreement (Verb Noun Agreement), Adjectives, Tenses, Pronoun, Preposition, Direct and Indirect Speech, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Completion (Fill in the blanks), Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Sentence Correction (Error Correction), Verbal Analogy (Word Based Analogy), Conjunction, Interjection, Verb, Articles, Adverb, Modals, Sentence Construction
  15. Live Classes Recordings(Earlier Batch): GATE 2026 Live Class
  16. Full Mock Test:
  17. Previous Year Papers:
  18. GATE 2026 Counselling: Counselling and Guidance Sessions
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video provides a detailed lecture on graph theory, specifically focusing on the concepts of minimum and maximum vertex degrees. The instructor begins by defining δ(G) as the minimum possible degree of any vertex in a graph and Δ(G) as the maximum possible degree. To illustrate these definitions, a specific graph with vertices labeled a through j is displayed alongside a table listing the degree of each vertex. The degrees range from 1 to 4. The instructor identifies the minimum degree as 1 and the maximum degree as 4. He then transitions to deriving a fundamental inequality that relates the number of vertices (|V|), the number of edges (|E|), and these degree measures. He writes out the lower bound inequality |V| × δ(G) ≤ 2|E| and substitutes the values from the example (10 × 1 ≤ 22). This sets the foundation for the final formula presented at the end of the lecture.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces the core definitions for the lesson. On the slide, text defines δ(G) as the minimum degree and Δ(G) as the maximum degree. A graph diagram is shown with vertices a, b, c, d, e, f, g, h, i, j. A table lists the degree for each vertex: a, b, c, f have degree 1; d, e have degree 4; g, h have degree 3; i, j have degree 2. The instructor writes δ(G) = 1 in blue ink, identifying the minimum value from the table. He then begins writing the inequality |V| × δ(G) ≤ 2|E|, preparing to substitute the graph's parameters.

  2. 2:00 – 3:51 02:00-03:51

    The lecture progresses to the upper bound of the inequality. The instructor writes 2|E| ≤ |V| × Δ(G) and calculates the right side as 10 × 4 = 40. He combines the lower and upper bounds into a single chain: |V| × δ(G) ≤ 2|E| ≤ |V| × Δ(G). Finally, he writes the formal notation δ(G) * |V(G)| ≤ 2|E| ≤ Δ(G) * |V(G)| on the board, circling the central term 2|E| to emphasize its role as the sum of degrees. This formula encapsulates the relationship between vertex degrees and edge count.

The video successfully guides students from basic definitions to a powerful graph theory inequality. By grounding the abstract concepts of δ(G) and Δ(G) in a concrete example with 10 vertices, the instructor makes the material accessible. The step-by-step derivation of the inequality |V| × δ(G) ≤ 2|E| ≤ |V| × Δ(G) demonstrates how the minimum and maximum degrees bound the total number of edges in a graph. This relationship is crucial for understanding graph properties, as it links local vertex characteristics (degree) to global graph characteristics (total edges). The final formula serves as a key takeaway, providing a mathematical constraint that must hold true for any graph.

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