Statistics is considered by many as another separate branch of mathematics and you can find a lot of video lectures devoted to the same. The course will emphasize p, This course is an introduction to probability as a language and set of tools for understanding statistics, science, risk, and randomness. selected problems on mathematical induction - Discrete Probability:Counting principles. R is a FreeVideoLectures aim to help millions of students across the world acquire knowledge, gain good grades, get jobs. Linear recurrence relations with constant coefficients (non-homogeneous case); discussion of several special cases to obtain particular solutions. Grant’s lectures are thorough and make discrete math seem easy. In our video lectures, we are going to talk about finite mathematics, differential equations, statistical probability, Laplace transforms, Fourier series and more. free software that is capable of handling mathemati, Learn everything from the basics of math, then test your knowledge with 510+ practice questions, Learn everything from Algebra 1 and Algebra 2, then test your knowledge with 1,300+ practice questions, Basic statistical analyses using the R program. Warshall's algorithm to compute transitive closure of a relation;Partially Ordered Sets and Lattices - Partial order relations; POSETS; lattices - Boolean Algebra and Boolean Functions Introduction to Boolean algebra and Boolean functions. Application to information theory: information and mutual information;Graph theory:Path, cycles, handshaking theorem, bipartite graphs, sub-graphs, graph isomorphism, operations on graphs, Eulerian graphs and Hamiltonian graphs, planar graphs, Euler formula, traveling salesman problem, shortest path algorithms;Relations:Definitions and properties; Equivalence relations and equivalence classes. For those who find it hard to understand, mathematics can be quite challenging. Important :Before downloading these lectures you need to install Real player Click on download link then ,it redirects to real player ... Institute: University Of Berkeley CA ,USA Instructor: John KUBIATOWICZ Lecture1. 3. 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FreeVideoLectures.com All rights reserved @ 2019, Any scientific task without the knowledge of software is difficult to imagine and complete in the current scenario. * Computer Sc - Discrete Mathematical Structures [NPTEL-IIT] * Discrete Mathematics - This has the prescribed book mentioned as Rosen. Lecture1. I especially enjoyed the reviews and quizzes that ensured I had retained information. 4.1 ( 11 ) Lecture Details. The text covers the mathematical concepts that students will encounter in many disciplines such as computer science, engineering, Business, and the sciences. Modular arithmetic and GCDs; applications include primality testing and crypto, Theorems of Rouche and Hurwitz:Fundamental Theorems Connected with Zeros of Analytic Functions - The Argument (Counting) Principle, Rouche's Theorem and The Fundamental Theore, Introductory - Mathematics in the Vedas and Sulva Sutras - Panini - Pingala - Mathematics in the Jaina Texts - Development of Place Value System - Aryabhatiya of Aryabhata - A, Pigeon hole Principle - Elementary Concepts - Elementary concepts and basic counting principles - Elementary concepts; Binomial theorem; Bijective proofs - Properties of binom, Set Theory:Introduction to the theory of sets; combination of sets; power sets; finite and infinite sets; principle of inclusion and exclusion; selected problems from each top, Initial Value Problems (IVP) and existence theorem. – Luke Mirman . We have video lectures for regression analysis, multivariate analysis, numerical analysis, computational techniques and more. Different representations of Boolean functions. Mathematics as a subject is vast and with these online tutorials, we have tried to segregate some major topics into distinct lectures. Discrete Mathematics Lectures ... Discrete Maths Lecture in Hindi by Easy Engineering Classes. This is why we have presented some of the best online lectures on mathematics where we will discuss a wide array of different topics. Blogger Template by 7:01. Lectures by Prof. Kamala Krithivasan, Department of Computer Science and Engineering, IIT Madras The course is taught in Python with Jupyter Notebooks, Introduction:Data Mining, Data Assimilation, Inverse problems and Prediction - Static vs. dynamic and deterministic vs. stochastic problems- formulation & classification;Mathe, Theorems of Picard, Casorati-Weierstrass and Riemann on Removable Singularities:Properties of the Image of an Analytic Function:Introduction to the Picard Theorems,Recalling S, Programming for numerical calculations, round-off error, approximation and interpolation, numerical quadrature, and solution of ordinary differential equations.

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