Quantitative Techniques

Quantitative techniques are those statistical and programming techniques, which help decision makers solve many problems, especially those concerning business and industry. It provides the decision makers with systematic and powerful means of analysis, based on quantitative data, for achieving predetermined goals. 

Books:

Introductory Methods of Numerical Methods, Vol-2, S.S.Shastri, PHI
Fundamentals of Mathematical Statistics, S.C.Gupta, V.K.Kapoor

Reference:

Elements of Applied Mathematics, Volume 1 and 2, P.N.Wartikar and J.N.Wartikar, A. V. Griha, Pune
Engineering Mathematics, Vol-2, S.S.Shastri, PHI
Applied Numerical Methods for Engineers using SCILAB and C, Robert J.Schilling and Sandra L.Harris, ” , Thomson Brooks/Cole

Practical List to be performed in Scilab:

Practical 1: Solution of algebraic and transcendental equations:

a. Program to solve algebraic and transcendental equation by bisection method.

b. Program to solve algebraic and transcendental equation by false position method.

c. Program to solve algebraic and transcendental equation by Newton Raphson method.

Practical 2: Interpolation

a. Program for Newton’s forward interpolation.

b. Program for Newton’s backward interpolation.

c. Program for Lagrange’s interpolation.

Practical 3: Solving linear system of equations by iterative methods:

a. Program for solving linear system of equations using Gauss Jordan methods.

b. Program for solving linear system of equations using Gauss Seidel methods.

Practical 4: Numerical Integration

a. Program for numerical integration using Trapezoidal rule.

b. Program for numerical integration using Simpson’s 1/3rd rule.

c. Program for numerical integration using Simpson’s 3/8th rule.

Practical 5: Solution of differential equations:

a. Program to solve differential equation using Euler’s method

b. Program to solve differential equation using modified Euler’s method.

c. Program to solve differential equation using Runge-kutta 2nd order and 4th order methods.

Practical 6: Random number generation and distributions

a. Program for random number generation using various techniques.

b. Program for fitting of Binomial Distribution.

c. Program for fitting of Poisson Distribution.

d. Program for fitting of Negative Binomial Distribution.

Practical 7: Moments, Correlation and Regression

a. Computation of raw and central moments, and measures of skewness and kurtosis.

b. Computation of correlation coefficient and Fitting of lines of Regression ( Raw and Frequency data )

c. Spearman’s rank correlation coefficient.

Practical 8: Fitting of straight lines and second degree curves

a. Curve fitting by Principle of least squares. ( Fitting of a straight line, Second degree curve)

 Practical 9: Sampling:

a. Model sampling from Binomial and Poisson Populations.

b. Model sampling from Uniform, Normal and Exponential Populations.

c. Large sample tests-( Single mean, difference between means, single proportion, difference between proportions, difference between standard deviations.)

d. Tests based on students ‘t-test’( Single mean, difference between means and paired ‘t’)

Practical 10: Chi-square test and LPP

a. Test based on Chi-square- Distribution ( Test for variance, goodness of Fit,)

b. Chi-square test of independence of attributes.

c. Solution of LPP by Simplex method.

For Any Programming Queries and Help Mail us at bscit.cracked999@gmail.com