MA3251 STATISTICS AND NUMERICAL METHODS Anna University Syllabus Regulation 21

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MA3251       STATISTICS AND NUMERICAL METHODS           L T P C 3 1 0 4

COURSE OBJECTIVES:

  • This course aims at providing the necessary basic concepts of a few statistical and numerical methods and give procedures for solving numerically different kinds of problems occurring in engineering and technology. 
  • To acquaint the knowledge of testing of hypothesis for small and large samples which plays an important role in real life problems.
  • To introduce the basic concepts of solving algebraic and transcendental equations.
  • To introduce the numerical techniques of interpolation in various intervals and numerical techniques of differentiation and integration which plays an important role in engineering and technology disciplines.
  • To acquaint the knowledge of various techniques and methods of solving ordinary differential equations.
     

 UNIT I                          TESTING OF HYPOTHESIS                                    9 + 3

 
Sampling distributions - Tests for single mean, proportion and difference of means (Large and small samples) – Tests for single variance and equality of variances – Chi square test for goodness of fit – Independence of attributes.

  UNIT II                         DESIGN OF EXPERIMENTS                                   9 + 3


One way and two way classifications - Completely randomized design – Randomized block design – Latin square design - 22 factorial design.

UNIT III   SOLUTION OF EQUATIONS AND EIGENVALUE PROBLEMS   9 + 3

 
Solution of algebraic and transcendental equations - Fixed point iteration method – Newton Raphson method- Solution of linear system of equations - Gauss elimination method – Pivoting - Gauss Jordan method – Iterative methods of Gauss Jacobi and Gauss Seidel - Eigenvalues of a matrix by Power method and Jacobi’s method for symmetric matrices.

 UNIT IV     INTERPOLATION, NUMERICAL DIFFERENTIATION 

                           AND NUMERICAL INTEGRATION                               9 +3

 
Lagrange’s and Newton’s divided difference interpolations – Newton’s forward and backward difference interpolation – Approximation of derivates using interpolation polynomials – Numerical single and double integrations using Trapezoidal and Simpson’s 1/3 rules.

UNIT V NUMERICAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS 9 +3

 
Single step methods: Taylor’s series method - Euler’s method - Modified Euler’s method - Fourth order Runge-Kutta method for solving first order differential equations - Multi step methods: Milne’s and Adams - Bash forth predictor corrector methods for solving first order differential equations.

COURSE OUTCOMES:
Upon successful completion of the course, students will be able to:

  • Apply the concept of testing of hypothesis for small and large samples in real life problems.
  • Apply the basic concepts of classifications of design of experiments in the field of agriculture.
  • Appreciate the numerical techniques of interpolation in various intervals and apply the numerical techniques of differentiation and integration for engineering problems.
  • Understandthe knowledge of various techniques and methods for solving first and second order ordinary differential equations.
  •  Solve the partial and ordinary differential equations with initial and boundary conditions by using certain techniques with engineering applications.

TEXT BOOKS:

  1. Grewal, B.S., and Grewal, J.S., "Numerical Methods in Engineering and Science", Khanna Publishers, 10th Edition, New Delhi, 2015.
  2. Johnson, R.A., Miller, I and Freund J., “Miller and Freund’s Probability and Statistics for Engineers", Pearson Education, Asia, 8th Edition, 2015.
REFERENCES:
  1.  Burden, R.L and Faires, J.D, "Numerical Analysis”, 9th Edition, Cengage Learning, 2016.
  2. Devore. J.L., "Probability and Statistics for Engineering and the Sciences”, Cengage Learning, New Delhi, 8th Edition, 2014.
  3.  Gerald. C.F. and Wheatley. P.O. "Applied Numerical Analysis” Pearson Education, Asia,New Delhi, 7th Edition, 2007.
  4.  Gupta S.C. and Kapoor V. K., “Fundamentals of Mathematical Statistics”, Sultan Chand & Sons, New Delhi, 12th Edition, 2020.
  5. Spiegel. M.R., Schiller. J. and Srinivasan. R.A., "Schaum’s Outlines on Probability and Statistics ", Tata McGraw Hill Edition, 4th Edition, 2012.
  6. Walpole. R.E., Myers. R.H., Myers. S.L. and Ye. K., “Probability and Statistics for Engineers and Scientists", 9th Edition, Pearson Education, Asia, 2010. 
 
  

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