MTH603 Midterm and Final term Solved Past Papers

An essential course that covers the theory, techniques, and algorithms required to solve mathematical problems numerically is MTH603, Numerical Analysis. The goal of this course is to give students a strong foundation in computational tools and numerical techniques that they will need to approximate solutions to a variety of mathematical problems that they will meet in science, engineering, and finance.

An introduction to error analysis and numerical computing is covered at the start of the course. Students gain knowledge of the causes of numerical computation errors, such as truncation and round-off errors, as well as methods for identifying, assessing, and reducing these errors. They also discuss the limitations of numerical precision and how to represent numbers in computers.

Numerical approximation methods for solving equations and locating function roots are among the main topics in MTH603. Students gain knowledge of iterative techniques for locating the roots of nonlinear equations, including the secant method, bisection method, and Newton-Raphson method. They look at methods for enhancing the effectiveness and resilience of root-finding algorithms, as well as convergence criteria and error quantification.

Numerical methods for function approximation and interpolation are also covered in the course. Students gain knowledge of spline interpolation techniques for curve fitting in addition to polynomial interpolation methods like Lagrange and Newton interpolation. They study the trade-offs between computational complexity and accuracy and discover which interpolation technique is best suited for a certain task.

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