{"id":22520,"date":"2020-07-12T02:55:16","date_gmt":"2020-07-12T02:55:16","guid":{"rendered":"https:\/\/www.inspirenignite.com\/vtu\/18ec44-engineering-statistics-linear-algebra-ece-syllabus-for-be-4th-sem-2018-scheme-vtu\/"},"modified":"2020-07-12T02:55:16","modified_gmt":"2020-07-12T02:55:16","slug":"18ec44-engineering-statistics-linear-algebra-ece-syllabus-for-be-4th-sem-2018-scheme-vtu","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/vtu\/18ec44-engineering-statistics-linear-algebra-ece-syllabus-for-be-4th-sem-2018-scheme-vtu\/","title":{"rendered":"18EC44: Engineering Statistics & Linear Algebra ECE Syllabus for BE 4th Sem 2018 Scheme VTU"},"content":{"rendered":"

Engineering Statistics & Linear Algebra detailed Syllabus for Electronics & Communication Engineering (ECE), 2018 scheme has been taken from the VTUs<\/a> official website and presented for the VTU students. For Course Code, Subject Names, Teaching Department, Paper Setting Board, Theory Lectures, Tutorial, Practical\/Drawing, Duration in Hours, CIE Marks, Total Marks, Credits and other information do visit full semester subjects post given below. The Syllabus PDF files can also be downloaded from the official website of the university.<\/p>\n

For all other VTU ECE 4th Sem Syllabus for BE 2018 Scheme, do visit VTU ECE 4th Sem Syllabus for BE 2018 Scheme <\/a>Subjects. The detailed Syllabus for engineering statistics & linear algebra is as follows. <\/p>\n

Course Learning Objectives:<\/h4>\n

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App<\/a>
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b>
\"Get<\/a>. <\/p>\n

Module-1<\/h4>\n

\nSingle Random Variables: Definition of random variables, cumulative distribution function continuous and discrete random variables; probability mass function, probability density functions and properties; Expectations, Characteristic functions, Functions of single Random Variables, Conditioned Random variables. Application exercises to Some special distributions: Uniform, Exponential, Laplace, Gaussian; Binomial, and Poisson distribution. (Chapter 4 Text 1) L1, L2, L3<\/p>\n

Module -2<\/h4>\n

\nMultiple Random variables: Concept, Two variable CDF and PDF, Two Variable expectations (Correlation, orthogonality, Independent), Two variable transformation, Two Gaussian Random variables, Sum of two independent Random Variables, Sum of IID Random Variables – Central limit Theorem and law of large numbers, Conditional joint Probabilities, Application exercises to Chi-square RV, Student-T RV, Cauchy and Rayleigh RVs. (Chapter 5 Text 1) L1, L2, L3<\/p>\n

Module-3<\/h4>\n

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App<\/a>
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b>
\"Get<\/a>. <\/p>\n

Module -4<\/h4>\n

\nVector Spaces: Vector spaces and Null subspaces, Rank and Row reduced form, Independence, Basis and dimension, Dimensions of the four subspaces, Rank-Nullity Theorem, Linear Transformations Orthogonality: Orthogonal Vectors and Subspaces, Projections and Least squares, Orthogonal Bases and Gram- Schmidt Orthogonalization procedure. (Refer Chapters 2 and 3 Text 2) L1, L2, L3<\/p>\n

Module -5<\/h4>\n

\nDeterminants: Properties of Determinants, Permutations and Cofactors. (Refer Chapter 4, Text 2) Eigenvalues and Eigen vectors: Review of Eigenvalues and Diagonalization of a Matrix, Special Matrices (Positive Definite, Symmetric) and their properties, Singular Value Decomposition. (Refer Chapter 5, Text 2) L1, L2, L3<\/p>\n

Course Outcomes:<\/h4>\n

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App<\/a>
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b>
\"Get<\/a>. <\/p>\n

Question Paper Pattern:<\/h4>\n

\n