## Analysis of Loops – Asymptotic Notation

Here, We learn about the analysis of loops like O(1), O(n), O(nc), O(log n), O(log log n) and O(m+n) in terms of time complexity and order of growth of functions in the algorithm.

Here, We learn about the analysis of loops like O(1), O(n), O(nc), O(log n), O(log log n) and O(m+n) in terms of time complexity and order of growth of functions in the algorithm.

Asymptotic Analysis of an algorithm refers to computing the running time of any operation in mathematical units of computation. We will learn about asymptotic analysis and notation, types of notation: big-o, omega & theta notation and growth rate of algorithm.

Algorithms Analysis help us to determine which algorithms are more efficient. Types of analysis:-Worst, Best, Average. How to Compare two Algorithms? Algorithm Complexity – Space Complexity, Time Complexity, Runtime Analysis of algorithms

Algorithms are a series of steps or rules for solving a computational problem. Here we learn categories, characteristics of algorithms, how to write algorithms with help of examples like write algorithm for the addition of two numbers

In a number of situation, we will to find factors of a given number. Some of the factors of a given number can be found very easily either by observation or by applying simple rules. We will look at some rules for divisibility of numbers: Divisibility by 2: A number divisible by 2 will have …

Numbers is one of the most important topics required for competitive entrance exams. It has been observed that Question paper has 20-30% question on number system. Classification of Numbers/Integers 1. Real Number: Real Number are classified into rational and irrational numbers. Rational Numbers: A number that can be expressed in the p/q where p and …