Sciences, Technology & Medicine

## Engineering Mathematics

Electronics & Communications (EC) Linear Algebra: Vector space, basis, linear dependence and independence, matrix algebra, eigen values and eigen vectors, rank, solution of linear equations â€“ existence and uniqueness. Calculus: Mean value theorems, theorems of integral calculus, evaluation of definite and improper integrals, partial derivatives, maxima and minima, multiple integrals, line, surface and volume integrals, Taylor series. Probability and Statistics: Mean, median, mode and standard deviation; combinatorial probability, probability distribution functions - binomial, Poisson, exponential and normal; Joint and conditional probability; Correlation and regression analysis. Electrical Engineering (EE) Linear Algebra: Matrix Algebra, Systems of linear equations, Eigenvalues, Eigenvectors. Calculus: Mean value theorems, Theorems of integral calculus, Evaluation of definite and improper integrals, Partial Derivatives, Maxima and minima, Multiple integrals, Fourier series, Vector identities, Directional derivatives, Line integral, Surface integral, Volume integral, Stokesâ€™s theorem, Gaussâ€™s theorem, Greenâ€™s theorem. Probability and Statistics: Sampling theorems, Conditional probability, Mean, Median, Mode, Standard Deviation, Random variables, Discrete and Continuous distributions, Poisson distribution, Normal distribution, Binomial distribution, Correlation analysis, Regression analysis. Instrumentation Engineering (IN) Linear Algebra: Matrix algebra, systems of linear equations, Eigen values and Eigen vectors. Calculus: Mean value theorems, theorems of integral calculus, partial derivatives, maxima and minima, multiple integrals, Fourier series, vector identities, line, surface and volume integrals, Stokes, Gauss and Greenâ€™s theorems. Probability and Statistics: Sampling theorems, conditional probability, mean, median, mode and standard deviation, random variables, discrete and continuous distributions: normal, Poisson and binomial distributions. Computer Science and Information Technology (CSIT) Linear Algebra: Matrices, determinants, system of linear equations, eigenvalues and eigenvectors, LU decomposition. Calculus: Limits, continuity and differentiability. Maxima and minima. Mean value theorem. Integration. Probability: Random variables. Uniform, normal, exponential, poisson and binomial distributions. Mean, median, mode and standard deviation. Conditional probability and Bayes theorem. Mechanical Engineering (ME) Linear Algebra: Matrix algebra, systems of linear equations, eigenvalues and eigenvectors. Calculus: Functions of single variable, limit, continuity and differentiability, mean value theorems, indeterminate forms; evaluation of definite and improper integrals; double and triple integrals; partial derivatives, total derivative, Taylor series (in one and two variables), maxima and minima, Fourier series; gradient, divergence and curl, vector identities, directional derivatives, line, surface and volume integrals, applications of Gauss, Stokes and Greenâ€™s theorems. Probability and Statistics: Definitions of probability, sampling theorems, conditional probability; mean, median, mode and standard deviation; random variables, binomial, Poisson and normal distributions. Civil Engineering (CE) Linear Algebra: Matrix algebra; Systems of linear equations; Eigen values and Eigen vectors. Calculus: Functions of single variable; Limit, continuity and differentiability; Mean value theorems, local maxima and minima, Taylor and Maclaurin series; Evaluation of definite and indefinite integrals, application of definite integral to obtain area and volume; Partial derivatives; Total derivative; Gradient, Divergence and Curl, Vector identities, Directional derivatives, Line, Surface and Volume integrals, Stokes, Gauss and Greenâ€™s theorems. Probability and Statistics: Definitions of probability and sampling theorems; Conditional probability; Discrete Random variables: Poisson and Binomial distributions; Continuous random variables: normal and exponential distributions; Descriptive statistics - Mean, median, mode and standard deviation; Hypothesis testing.
• Publisher: VIDYALANKAR
• Language: English
• Chapter 1

### LINEAR ALGEBRA Price 0.30  |  0.3 Rewards Points

DETERMINANTS MINORS & CO-FACTORS PRODUCT OF DETERMINANTS (JACOBI THEOREM) MATRICES RANK OF A MATRIX ORTHOGONAL MATRIX VECTORS EIGEN VALUES EIGEN VECTORS
• Chapter 2

### CALCULUS Price 0.30  |  0.3 Rewards Points

Taylorâ€™s Theorem Fourier Series Limit and Continuity Partial Derivatives Integration Definite Integrals Improper Integrals Double Integrals Triple Integrals List of Formulae
• Chapter 3

### PROBABILITY Price 1.20  |  1.2 Rewards Points

Probability Permutation Combinations Conditional Probability Bayeâ€™s Rule Random Variables and Distributions Standard Distributions Weibull Distribution The Method of Least Squares Analysis of Variance List of Formulae
• Chapter 4

### SOLUTIONS-ENGINEERING MATHEMATICS Price 0.30  |  0.3 Rewards Points

Solutions to Linear Algebra, Calculus and Probability Assignments.