Polynomial Functions
Duration: 3 min
This video lesson is available to enrolled students.
Inside: a video lesson and guided study material.
Module outline
- About Course: About the Course
- Paper 1 | General Studies: State Wise GK
- Paper 1 | Information and Communication Technology: Role of Internet and Web Services, Security in Mobile and Wireless Computing
- Paper 1 | Current Affairs: GK- Current Affairs
- Paper 2 | Discrete Mathematical Structure: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic, Probability
- Paper 2 | Digital Computer Organization And Architecture: Number System, Number Representation, Sequential Circuits, Combinational Circuit, Basics of COA, Floating Point Rep, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Register Transfer and Microoperations, Control Unit Design, Programming the Basic Computer
- Paper 2 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
- Paper 2 | Programming Languages & Object-Oriented Programming Concepts: Java, OOPS with C++, Java Fundamentals, Array, String, IO & References
- Paper 2 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis
- Paper 2 | Data Structure And Algorithms: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Minimum Spanning Trees, Advanced Algorithms
- Paper 2 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Unix OS
- Paper 2 | Theory Of Computation: 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
- Paper 2 | 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
- Paper 2 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, Relational Algebra, SQL, Transaction Management, Concurrency Control, Database Recovery, Database Security & Authorization, Enhanced Data Models
- Paper 2 | Computer Network And Information Security: Introduction to CN, Data Communication, Application Layer, Hardware basics, Cyber Threats and Malware Attacks, Network Security, 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
- Paper 2 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
- Paper 2 | Current Trends & Technologies: Emerging Tech Trends, Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Planning, Multi Agent Systems, Fuzzy Sets, Natural Language Processing, Artificial Neural Networks, Genetic Algorithms, Artificial Intelligence, Data Warehousing & Mining, Electronic Data Interchange and E-Commerce, Terms & Abbreviations
- Paper 2 | Full Length Mock Tests:
AI summary & chapters
AI Summary
An AI-generated summary of this video lecture.
This lecture segment introduces polynomial functions and their growth rates as n approaches infinity. The instructor presents a core example problem requiring students to arrange six specific functions in increasing order of growth: sqrt(n), n, n^2, n log n, n^3, and n^k (where k >= 1). The teaching method emphasizes rewriting radical expressions as fractional exponents to facilitate direct comparison of polynomial powers. For instance, the square root function is explicitly converted from sqrt(n) to n^0.5 or n^(1/2). The instructor systematically compares terms by analyzing their exponents and logarithmic factors, establishing a hierarchy where lower powers grow slower than higher powers. The visual progression shows the instructor underlining terms, circling intermediate comparisons like 5n versus n, and highlighting the final sorted sequence in a pink box. Key concepts include identifying that polynomial growth dominates logarithmic-linear terms, and that higher exponents indicate faster asymptotic growth.
Chapters
0:00 – 2:00 00:00-02:00
The instructor introduces the topic of polynomial functions and presents an example problem asking to arrange a set of functions in increasing order of growth as n approaches infinity. The visible text on screen lists the target functions: sqrt(n), n, n^2, n log n, n^3, and n^k. The instructor begins by analyzing the first function, square root of n, rewriting it as a power of n (n^0.5) to facilitate comparison with the other polynomial and logarithmic terms. This conversion is a critical step shown in the notes, where n^0.5 = n^(1/2) is written to standardize the notation for exponent comparison.
2:00 – 3:30 02:00-03:30
The instructor continues the analysis by comparing linear terms against logarithmic factors to establish the hierarchy between n, n log n, and n^2. The visual notes show comparisons like 5n versus n and the analysis of n log n versus n^2 to determine their relative magnitudes. The progression shows a step-by-step comparison of terms, circling them to indicate order. Finally, the sorted sequence is highlighted in a pink box on screen: sqrt(n), n, n log n, n^2, n^3, n^k. This final arrangement demonstrates the hierarchy of growth rates from the lowest power (n^0.5) up to the highest polynomial term (n^k), confirming that polynomial functions with higher exponents grow faster than those with lower exponents or logarithmic multipliers.
The lecture effectively demonstrates the method for comparing asymptotic growth rates of polynomial and related functions. The central technique involves converting all terms to a standard exponential form, such as rewriting sqrt(n) as n^0.5, which allows for direct comparison of the exponents. The instructor establishes a clear hierarchy where n^0.5 grows slower than n, which in turn grows slower than n log n, followed by higher powers like n^2 and n^3. The final sorted sequence provided in the pink box serves as a definitive reference for students to understand that among polynomial functions, the magnitude of the exponent dictates the growth rate. This example reinforces the fundamental concept that as n approaches infinity, higher powers dominate lower powers and logarithmic factors.