Lectures related to Error Estimation in Numerical Integration

Covers Newton-Cotes integration, Trapezoid rule, Simpson rules, and numerical quadrature conditioning.

Explores the Method of Moments, Bias-Variance tradeoff, Consistency, Plug-In Principle, and Likelihood Principle in point estimation.

Covers quadrature methods, focusing on composite and non-composite techniques, their formulas, and practical applications in integration.

Explores the composite quadrature formula, digital integration, and numerical integration techniques using interpolating polynomials.

Covers numerical integration techniques and their applications in various scientific and engineering fields.

Covers the probabilistic model for linear regression and its applications in nuclear magnetic resonance and X-ray imaging.

Covers the Crank-Nicolson and Heun's methods, discussing uniqueness of solutions and truncation errors in numerical methods.