UNIT 1:
t-distribution -Difference of mean
t-distribution – Single mean
Introduction ,Sampling distribution estimation of parameters
Large sample test based on Normal distribution- single mean
Large sample test -difference of means
Chi square -Goodness of fit.
Chi square -Independence of attributes
UNIT 2:
Introduction and application of design of experiments
One-way classifications - Completely randomized design
One-way classifications - Completely randomized design
Two-way classification-Randomized block design
Two-way classification-Randomized block design
UNIT 3:
Introduction - Newton Raphson method
Pivoting Gauss Jordan method
Gauss Seidal Iterative method
Gauss Seidal Iterative method
Matrix Inversion – Gauss Jordan method
Eigen values of a matrix by power method.
Eigen values of a matrix by power method.
UNIT 4:
Introduction of application of Numerical differentiation and integration
Problems on Lagrange’s Interpolation
Newton’s forward and backward interpolation
Problems on Newton’s interpolation
Approximation of derivates using interpolation
Numerical integration by Trapezoidal
Numerical integration by Simpson’s 1/3 rules.
Problems on Trapezoidal and Simpson’s 1/3 rules.
UNIT 5:
Integration and application of Numerical solution of ODE
Taylor’s series method for solving I order ODE
Euler’s & Modified Euler’s method
Problems on Euler’s & Modified Euler’s method
Fourth order Runge-Kutta method for solving first order equations
Fourth order Runge-Kutta method for solving first order equations
Milne’s predictor corrector methods for solving first order
Adam’s- Bash forth predicator formula
