Error analysis (mathematics)

Related lectures (30)

Page 2 of 3

Covers the concept of numerical derivatives of order 2 and the error analysis involved.

Discusses numerical derivatives of order 1 and the effects of rounding errors on calculations.

Discusses the explicit Runge Kulta method for function approximation and error analysis.

Explores the concepts of linear and quadratic convergence rates, highlighting their differences and applications in numerical methods.

Explores numerical computing stability, error analysis, and truncation error impact.

Discusses evaluation feedback, convergence, error analysis, and adaptive time steps in physics simulations.

Covers error analysis, stability, and adaptive time stepping in numerical methods, including convergence order and equilibrium points.

Covers numerical integration methods, focusing on trapezoidal rules, degree of exactness, and error analysis.

Discusses the bisection method for solving nonlinear equations and its implementation using Python with NumPy and Matplotlib.

Covers the Simpson quadrature rule for numerical integration, explaining the method to compute integrals using interpolation nodes and weights.