جبر خطي - الجزء الأول math 244
math 244 part 2
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CHAPTER 1 System of Linear Equation and Matrices
- 1.1 Linear Equation 12:45
- 1.1 Solution of System of Linear Equations 10:25
- 1.1 Number of Solution 14:17
- 1.1 Solving The System of Linear Equation 08:53
- 1.1 Solving The System of Linear Equation (infintly many solution) 13:02
- 1.1 Augmented Matrices and Elementary Row Operations 08:31
- 1.1 Using Elementary Row Operations 20:45
- 1.2 What We Are Going To Do? 05:19
- 1.2 Echelon Form 10:00
- 1.2 Examples for Echelon Form 06:26
- 1.2 Solution from Echelon Form Part1 03:08
- 1.2 Solution from Echelon Form Part2 09:57
- 1.2 Gauss and Gauss Jordan Methods 18:24
- 1.2 Solve By Gauss 13:54
- 1.2 Solve By Gauss Jordan 09:38
- 1.2 Example 5 18:34
- 1.2 Homogeneous Linear System 05:50
- 1.2 Solving Homogeneous Linear System 03:51
- 1.2 Free Variable Theorem 05:52
- 1.2 Back Substitution 06:02
- 1.2 Example 8 03:42
- 1.2 Some Fact About Echelon Form 05:00
- 1.3 Introduction to Matrices 06:34
- 1.3 More About Matrices 07:11
- 1.3 Equal Matrices 03:20
- 1.3 Adding Two Matrices 05:29
- 1.3 Scalar Multiple 05:08
- 1.3 Multiplying Two Matrices 11:46
- 1.3 Examples of Multiplying Two Matrices 07:32
- 1.3 Matrix Multiplication by Columns and by Rows 06:48
- 1.3 Example 7 04:32
- 1.3 Linear Combinations of Matrices 03:31
- 1.3 Theorem 1.3.1 05:12
- 1.3 Example 9 03:08
- 1.3 Columns-Rows Expansion 06:16
- 1.3 Matrix Form of a Linear System 02:20
- 1.3 Transpose of a Matrix 04:38
- 1.3 Trace of a Matrix 03:09
- 1.4 Properties of Matrices 07:50
- 1.4 Properties of Matrix Multiplication 05:37
- 1.4 Zero Matrix and It's Properties 04:34
- 1.4 Cancellation Law and Zero Product in Matrices 05:28
- 1.4 Identity Matrix 06:47
- 1.4 Theorem 1.4.3 02:24
- 1.4 Inverse of a Matrix 09:16
- 1.4 Uniqueness of Inverse 05:06
- 1.4 Finding The Inverse of 2x2 Matrices 08:47
- 1.4 Example 7 03:19
- 1.4 Example 8 02:23
- 1.4 Product of Invertible Matrices 06:38
- 1.4 Powers of a Matrix Part 1 06:14
- 1.4 Powers of a Matrix Part 2 06:45
- 1.4 Matrix Polynomial 03:42
- 1.4 Properties of Transpose 08:02
- 1.5 Inverse Row Operation 07:52
- 1.5 Elementary Matrix 06:07
- 1.5 Row Operation by Matrix Multiplication 08:22
- 1.5 Inverse Operations in Elementary Matrix 07:26
- 1.5 Equivalent Statement 06:47
- 1.5 Using Row Operations to Find the Inverse 09:12
- 1.5 Showing That a Matrix Is Not Invertible 04:45
- 1.6 Solving Linear System By Inverse of Matrix 08:21
- 1.6 Solving Many Linear System at Once 08:33
- 1.6 More Properties of Invertible Matrices 03:47
- 6.1 Determining Consistency 12:09
- 1.7 Diagonal Matrix 11:07
- 1.7 Triangular Matrix 08:58
- 1.7 Symmetric Matrices 10:50
- 1.7 Product of a Matrix With its Transpose 09:03
- 1.8 Matrix Transformation 12:46
- 1.8 Standard Matrix 15:21
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CHAPTER 2 Determinants
- 2.1 Minors And Cofactors 17:16
- 2.1 Definition of a General Determinant 10:09
- 2.1 Smart Choice of Row and Column 09:03
- 2.1 Determinant of Triangular Matrix 04:58
- 2.1 Evaluating of 3X3 Determinants 05:04
- 2.2 Basic Theorems 03:02
- 2.2 Elementary Row Operations 09:09
- 2.2 Determinant of Elementary Matrices 06:49
- 2.2 Matrices with Proportional Rows or Columns 05:46
- 2.2 Evaluating Determinant by Row Reduction 04:54
- 2.2 Extra Examples 04:38
- 2.2 Another Ways to Evaluate Determinant 09:06
- 2.3 determinant KA 05:26
- 2.3 det(A+B) 07:10
- 2.3 det(AB) 02:42
- 2.3 Determinant Test for Invertibilty 06:01
- 2.3 Entries and Cofactor From Different Rows 05:56
- 2.3 Adjoint Matrix 08:11
- 2.3 Using the Ajoint to Find an Inverse Matrix 03:56
- 2.3 Cramer's Rule 09:28
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CHAPTER 3 Euclidean Vector Spaces
- 3.1 Introduction to Victors 04:44
- 3.1 Operations on Vectors 09:05
- 3.1 Vectors in Coordinate Systems 08:44
- 3.1 n-Space 09:52
- 3.1 Linear Combinations 05:39
- 3.2 Norm of a Vector 07:06
- 3.2 Unit Vector 05:14
- 3.2 Standard Unit Vectors 12:11
- 3.2 Distance in n-Space 04:42
- 3.2 Dot Product Part 1 09:20
- 3.2 Dot Product Part 2 04:21
- 3.2 Algebraic Properties for Dot Product 06:26
- 3.2 Cauch - Schwarz Inequality 05:43
- 3.2 Parallelogram Equation for a Vector 05:20
- 3.2 Dot Product as Matrix Multiplication 07:18
- 3.2 Example 9 08:21
- 3.3 Orthogonality 07:10
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CHAPTER 4 General Vector Spaces
- 4.1 Vector Space 08:43
- 4.1 Examples of Vector Space 10:44
- 4.1 More Examples of Vector Space 07:58
- 4.1 The Vector Space of Real Valued Function 09:49
- 4.1 A Set that is Not a Vector Space 04:30
- 4.1 An Unusual Vector Space 12:12
- 4.1 Exercise 11 11:02
- 4.1 Extra Example of a Set that is Not a Vector Space 08:38
- 4.2 The Meaning of subspace 07:25
- 4.2 Subspaces of R2 10:10
- 4.2 Subspaces of R3 and Mnn 09:26
- 4.2 Subspaces of Funations 09:12
- 4.2 Linear Combination 06:31
- 4.2 Example ( Is w a linear combination of Other Vectors ? ) 11:57
- 4.2 Spanning Set 11:55
- 4.2 Testing for Spanning 12:19
- 4.2 Equal Spanning Sets 04:26
- 4.2 The Solution of a Homogeneous linear System 04:05
- 4.2 Solution Spaces of Homogeneous Linear System 07:20
- 4.2 Matrix Transformation 03:35
- 4.3 Linearly independence 22:18
- 4.3 Linearly Independent of Polynomials 13:32
- 4.3 Wronskian 14:49
- 4.4 Basis 13:27
- 4.4 Uniqueness of Basis Representation 06:51
- 4.4 Coordinates 09:29
- 4.5 Dimension 09:53
- 4.5 Plus Minus Theorem 26:05
- 4.7 Row Space, Vector Space, Null Space 07:56
- 4.7 The Relationship Between Ax=b and col(A) and null(A) 16:03
- 4.7 Basis of null(A) 08:46
- 4.7 Basis for row(A) and Col(A) 10:38
- 4.7 Basis for the Space Spanned by a Set of Vectors 14:53
- 4.7 summarize 05:14
- 4.8 Rank and nullity 08:52
- 4.8 Some Theorems about Rank and nullity 11:30
- 4.8 The fundamental spaces of a Matrix 07:19
- 1.8 Matrix Transformation 12:46
- 1.8 Standard Matrix 15:21
- 4.8 Overdetermind and underdetermind 12:32
- 4.9 Reflection Operator 13:28
- 4.9 Projection Operator 15:50
- 4.9 Dilation and Contraction 08:34
- 4.10 Composition of Matrix Transformation 09:13
- 4.10 Examples of Composition 19:41
- 4.10 One-to-one Matrix Transformation 07:03
- 4.10 Kernel and Range 10:40
- 4.10 Inverse Operator 09:59
- 4.6 Change of Basis (Basic Idea) 18:34
- 4.6 Invertibility of Transition Matrix - Learning New Procedure to Compute Transition Matrix 10:52
- 4.6 Finding Transition Matrix and Computing coordinates vectors (Example 1 and 2) 18:52
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Exercises
- 1.1 Introduction to Systems of Linear Equations part1 09:53
- 1.1 Introduction to Systems of Linear Equations part2 13:06
- 1.1 Introduction to Systems of Linear Equations part3 10:34
- 1.1 Introduction to Systems of Linear Equations part4 15:48
- 1.2 Gaussian Elimination part 1 09:45
- 1.2 Gaussian Elimination part 2 07:40
- 1.2 Gaussian Elimination part 3 05:14
- 1.2 Gaussian Elimination part 4 10:30
- 1.2 Gaussian Elimination part 5 10:41
- 1.2 Gaussian Elimination part 6 08:49
- 1.2 Gaussian Elimination part 7 11:25
- 1.2 Gaussian Elimination part 8 13:03
- 1.3 Matrices and Matrix Operations Part 1 08:43
- 1.3 Matrices and Matrix Operations Part 2 08:33
- 1.3 Matrices and Matrix Operations Part 3 12:34
- 1.3 Matrices and Matrix Operations Part 4 12:51
- 1.3 Matrices and Matrix Operations Part 5 08:50
- 1.4 Inverses;Algebraic Properties of Matrices Part 1 08:35
- 1.4 Inverses;Algebraic Properties of Matrices Part 2 13:17
- 1.4 Inverses;Algebraic Properties of Matrices Part 3 13:44
- 1.5 Elementary Matrices and a Method for Finding the Inverse Part 1 11:28
- 1.5 Elementary Matrices and a Method for Finding the Inverse Part 2 19:14
- 1.5 Elementary Matrices and a Method for Finding the Inverse Part 3 17:12
- 1.6 More on Linear Systems and Invertible Matrices Part 1 10:36
- 1.6 More on Linear Systems and Invertible Matrices Part 2 10:58
- 1.6 More on Linear Systems and Invertible Matrices Part 3 16:55
- 1.7 Diagonal, Triangular, Symmetric Matrices 30:19
- 1.8 Matrix Transformations 21:12
- 2.1 Determinants by Cofactor Expansion Part 1 13:28
- 2.1 Determinants by Cofactor Expansion Part2 17:55
- 2.1 Addition, Scalar Multiplication, Multiplication of Matrices Part 3 15:33
- 2.2 Evaluating Determinant by Row Reduction Part 1 07:30
- 2.2 Evaluating Determinant by Row Reduction Part 2 10:28
- 2.2 Evaluating Determinant by Row Reduction Part 3 12:32
- 2.3 Properties of Determinant, Cramer's Rule Part 1 12:22
- 2.3 Properties of Determinant, Cramer's Rule Part 2 16:05
- 2.3 Properties of Determinant, Cramer's Rule Part 3 07:30
- 2.3 Properties of Determinant, Cramer's Rule Part 4 06:50
- 3.1 Vectors in 2-Space, 3-Space and n-Space Part 1 11:42
- 3.1 Vectors in 2-Space, 3-Space and n-Space Part 2 07:12
- 3.2 Norm, Dot Product and distance in n-Space Part 1 12:10
- 3.2 Norm, Dot Product and distance in n-Space Part 2 13:52
- 3.3 Orthogonality Part 1 07:33
- 3.3 Orthogonality Part 2 08:49
- حل أسئلة سابقة
- Five Questions Tutorial
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Exercises
- 1.1 Introduction to Systems of Linear Equations part1 09:53
- 1.1 Introduction to Systems of Linear Equations part2 13:06
- 1.1 Introduction to Systems of Linear Equations part3 10:34
- 1.1 Introduction to Systems of Linear Equations part4 15:48
- 1.2 Gaussian Elimination part 1 09:45
- 1.2 Gaussian Elimination part 2 07:40
- 1.2 Gaussian Elimination part 3 05:14
- 1.2 Gaussian Elimination part 4 10:30
- 1.2 Gaussian Elimination part 5 10:41
- 1.2 Gaussian Elimination part 6 08:49
- 1.2 Gaussian Elimination part 7 11:25
- 1.2 Gaussian Elimination part 8 13:03
- 1.3 Matrices and Matrix Operations Part 1 08:43
- 1.3 Matrices and Matrix Operations Part 2 08:33
- 1.3 Matrices and Matrix Operations Part 3 12:34
- 1.3 Matrices and Matrix Operations Part 4 12:51
- 1.3 Matrices and Matrix Operations Part 5 08:50
- 1.4 Inverses;Algebraic Properties of Matrices Part 1 08:35
- 1.4 Inverses;Algebraic Properties of Matrices Part 2 13:17
- 1.4 Inverses;Algebraic Properties of Matrices Part 3 13:44
- 1.5 Elementary Matrices and a Method for Finding the Inverse Part 1 11:28
- 1.5 Elementary Matrices and a Method for Finding the Inverse Part 2 19:14
- 1.5 Elementary Matrices and a Method for Finding the Inverse Part 3 17:12
- 1.6 More on Linear Systems and Invertible Matrices Part 1 10:36
- 1.6 More on Linear Systems and Invertible Matrices Part 2 10:58
- 1.6 More on Linear Systems and Invertible Matrices Part 3 16:55
- 1.7 Diagonal, Triangular, Symmetric Matrices 30:19
- 2.1 Determinants by Cofactor Expansion Part 1 13:28
- 2.1 Determinants by Cofactor Expansion Part2 17:55
- 2.1 Addition, Scalar Multiplication, Multiplication of Matrices Part 3 15:33
- 2.2 Evaluating Determinant by Row Reduction Part 1 07:30
- 2.2 Evaluating Determinant by Row Reduction Part 2 10:28
- 2.2 Evaluating Determinant by Row Reduction Part 3 12:32
- 2.3 Properties of Determinant, Cramer's Rule Part 1 12:22
- 2.3 Properties of Determinant, Cramer's Rule Part 2 16:05
- 2.3 Properties of Determinant, Cramer's Rule Part 3 07:30
- 2.3 Properties of Determinant, Cramer's Rule Part 4 06:50
- 3.1 Vectors in 2-Space, 3-Space and n-Space Part 1 11:42
- 3.1 Vectors in 2-Space, 3-Space and n-Space Part 2 07:12
- 3.2 Norm, Dot Product and distance in n-Space Part 1 12:10
- 3.2 Norm, Dot Product and distance in n-Space Part 2 13:52
- 3.3 Orthogonality Part 1 07:33
- 3.3 Orthogonality Part 2 08:49
- 4.1 Real Vector Spaces Part 1 18:48
- 4.1 Real Vector Spaces Part 2 15:44
- 4.1 Real Vector Spaces Part 3 23:15
- 4.2 Subspaces Part 1 24:22
- 4.2 Subspaces Part 2 17:06
- 4.2 Subspaces Part 3 24:50
- 4.3 Linear Independence Part 1 24:24
- 4.3 Linear Independence Part 2 22:30
- 4.4 Coordinates and Basis Part 1 18:08
- 4.4 Coordinates and Basis Part 2 09:59
- 4.5 Dimension 19:36
- 4.7 Row Space, Vector Space, Null Space 26:22
- 4.8 Rank, Nullity and the Fundamental Matrix Spaces 24:30
- 4.9 Basic Matrix Transformation 15:19
- 9.10 Properties of Matrix Transformation Part 1 26:13
- 9.10 Properties of Matrix Transformation Part 2 15:36
- 5.1 Eigenvalue and Eigenvectors Part 1 16:12
- 5.1 Eigenvalue and Eigenvectors Part 2 15:32
- 4.6 Change of Basis 18:54
- 5.2 Diagonalization 45:45
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CHAPTER 1 System of Linear Equation and Matrices
- math 244 part 2
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• Hadeel Mohammed Almadiny. • Lecturer in Vision Academy. • Specialty in mathematics. • Graduated from (KSU)with calss honor. ~ Experiences: • teacher in international school. • English language. • Strategic teaching course. ~ Achievements: • Title of scientific meeting leader in KSU.
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