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Description 0
This series is completely for beginners if you don't know the basics its completely fine then also you can easy learn from this series and understand the complex concept of maths 4 in a easy way
Branches Covered ( Comps , Mechanical , Civil , EXTC , Electrical , Electronics )
Handmade Notes : Notes are Brilliant , Easy Language , East to understand ( Student Feedback )
Exam ke Pehle Notes ek baar Dekhlo revision aise hi jata hai
Complex Integration
Matrices / Linear Algebra : Matrix Theory
Probability
Sampling
Mathematical Programming
Vector Calculus (Mech /Civil )
Linear Programming ( Mech /Civil )
Correlation (EXTC/Electrical/Electronics)
Coming Soon
Nonlinear Programming
Calculus of Variation
Linear Algebra : Vector spaceNo items in this section -
Complex Integration 7
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Complex integration along a Line or Parabola with Solved Example 17 minLecture2.1
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Complex integration along a Circle with Solved Example 12 minLecture2.2
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Cauchy’s Theorem Basics & Cauchy’s integral formula Type 1 13 minLecture2.3
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Cauchy’s Theorem Type 2 and Type 3 10 minLecture2.4
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Cauchy’s Theorem Type 4 and Type 5 12 minLecture2.5
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Taylor and Laurent series Full Basic with Solved Example part 1 15 minLecture2.6
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Taylor and Laurent series Full Basic with Solved Example part 2 17 minLecture2.7
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Probability Distribution 14
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Introduction to Probability Distribution 07 minLecture3.1
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Discrete Random Variable in Probability Distribution 15 minLecture3.2
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Distribution function of Discrete Random Variable 10 minLecture3.3
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Continuous Random Variable in Probability Distribution 09 minLecture3.4
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Continuous Distribution Function in Probability Distribution 14 minLecture3.5
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Expectation in Probability Distribution 12 minLecture3.6
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Mean and Variance Part 1 in Probability Distribution 11 minLecture3.7
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Mean and Variance Part 2 in Probability Distribution 13 minLecture3.8
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Moments and Moments Generating Function Part #1 in Probability Distribution 13 minLecture3.9
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Moments and Moments Generating Function Part #2 in Probability Distribution 11 minLecture3.10
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Binomial Probability Distribution 18 minLecture3.11
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Poisson Distribution with Solved Example 11 minLecture3.12
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Normal Distribution Full Basic Concept 12 minLecture3.13
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Normal distribution with Solved Example 20 minLecture3.14
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Linear Algebra / Matrices 11
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Introduction to Matrices 07 minLecture4.1
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Eigen value and Eigen vector in Matrices 17 minLecture4.2
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Eigen value and Eigen vectors for Types of Matrices 06 minLecture4.3
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Cayley Hamilton Theorem with Example Part 1 09 minLecture4.4
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Cayley Hamilton Theorem with Example Part 2 05 minLecture4.5
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Cayley Hamilton Theorem with Example Part 3 04 minLecture4.6
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Monic and Minimal Polynomial of a Matrix 05 minLecture4.7
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Algebraic multiplicity And Geometric multiplicity 10 minLecture4.8
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Functions of a Square Matrix in Matrices 07 minLecture4.9
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Reduction of Quadratic form to Canonical form 13 minLecture4.10
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Orthogonal Matrix with Solved Example 09 minLecture4.11
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Sampling Theory 11
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What Is Sampling 08 minLecture5.1
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Large Sampling Problems 16 minLecture5.2
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Large Sampling Test Theory+Numerical 16 minLecture5.3
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Hypothesis Testing Full concept 02 minLecture5.4
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Testing Difference Between Means(case_1) With Examples 11 minLecture5.5
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Small Sample Test Example 13 minLecture5.6
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Small Sample Test 04 minLecture5.7
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Testing Difference Between Means(case_1) With Examples Part 2 05 minLecture5.8
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Testing Difference Between Means(case_2) 12 minLecture5.9
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Non Parametric Test Type_1_Numerical 08 minLecture5.10
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Non Parametric Test 04 minLecture5.11
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Mathematical Programming / Linear Programming 8
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Basics of simplex method in LPP 11 minLecture6.1
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Standard form of LPP Simplex Method 12 minLecture6.2
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Types of Solutions in Simplex Method in LPP 14 minLecture6.3
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How to Solve LPP using Simplex method 18 minLecture6.4
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LPP Using Big M method ( Penalty Method ) 25 minLecture6.5
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Duality of LPP ( Primal and Dual ) 17 minLecture6.6
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Relationship between Primal and Dual 17 minLecture6.7
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Dual Simplex Method in LPP 17 minLecture6.8
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Vector Calculus 6
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Divergence and curl 10 minLecture7.1
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Scalar Potential 14 minLecture7.2
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Vector differentiation basics and gradient 15 minLecture7.3
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Green theorem 15 minLecture7.4
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Gauss divergence theorem 07 minLecture7.5
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Stokes Theorem 17 minLecture7.6
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Calculus of Variation 11
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Euler’s Differential Equation 11 minLecture8.1
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Functions of Second Order Derivative 09 minLecture8.2
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Gram Schmidt Process With Numerical 19 minLecture8.3
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Hypothesis Concerning Several Proportions 07 minLecture8.4
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Linear Combinations Of Vector 05 minLecture8.5
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Non Parametric Test Type_2_Numerical 05 minLecture8.6
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Pythagorean Theorem 04 minLecture8.7
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Subspaces 10 minLecture8.8
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Cauchy Schwarz Inequality in R^ 05 minLecture8.9
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Lagranges Method 09 minLecture8.10
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Rayleigh Ritz Method 12 minLecture8.11
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Correlation (EXTC, Electrical , Electronics) 3
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Introduction to correlation 08 minLecture9.1
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Karl Pearson coefficient correlation 06 minLecture9.2
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Spearman Rank 13 minLecture9.3
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Regression (EXTC, Electrical , Electronics) 3
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Introduction to Regression 05 minLecture10.1
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Regression part 2 13 minLecture10.2
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Regression part 3 15 minLecture10.3
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Notes 10
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Complex Integration NotesLecture11.1
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Matrices NotesLecture11.2
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Probability NotesLecture11.3
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Sampling Theory NotesLecture11.4
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Linear Programming Problems NotesLecture11.5
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Calculus of Variation (EXTC, Electrical , Electronics Notes)Lecture11.6
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Linear Algebra Vector Space (EXTC, Electrical , Electronics Notes )Lecture11.7
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Correlation,Regression and Curve Fitting (EXTC, Electrical , Electronics Notes )Lecture11.8
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Graph and Group theory (IT)Lecture11.9
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Lattice theory (IT)Lecture11.10
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Solution Keys 5
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Solution Key module 1Lecture12.1
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Practice problems solution key matricesLecture12.2
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Practice problem solution key for ProbabilityLecture12.3
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Solution key for Sampling TheoryLecture12.4
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Linear Programming solution keyLecture12.5
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Z transform 8
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Introduction to Z transform 16 minLecture13.1
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Z Transforms Change Of Scale 05 minLecture13.2
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Z Transforms Linearity 09 minLecture13.3
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Z Transforms multiplication by k 10 minLecture13.4
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Z Transforms Of Standard Functions 08 minLecture13.5
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Z Transforms Shifting Property 05 minLecture13.6
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Inverse Z transform using binomial expansion 08 minLecture13.7
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Inverse Z transform using partial fractions 20 minLecture13.8
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Regression part 3