Informatyka w chemii (+USOS) 0600-S1-O-IC
Wykład (WYK) Semestr zimowy 2021/22

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Lecture:

1. Introductory lecture

2. USOS training

3. Introduction to statistical analysis of experimental data, significant digits (figures), statistical analysis of random error, uncertainty of measurement, type B evaluation of uncertainty,

4. Propagation of uncertainty, type A evaluation of uncertainty, combined standard uncertainty

5. Linear regression – least square method, weighted linear regression, analysis of residuals, linearizing transformations

6. Non-linear regression – polynomial equation fitting

7. Multiple linear regression analysis, regression coefficients, selecting variables – stepwise procedures

8. Numerical integration, integral and its geometric interpretation, rectangle method, trapezoidal method, Simpson’s rule method, Gauss–Legendre method.

9. Fundamentals of numerical solving of differential equations, Euler method, Runge–Kutta method, Milne method (predictor-corrector)

10. . Methods for solving algebraic equations ,bisection method, secant method (regula falsi), tangent method (Newton-Raphson)

11. Methods for solving systems of linear equations, Matrix calculus – fundamentals, Cramer method, GaussSeidel method, GaussJordan elimination method, NewtonRaphson method for nonlinear algebraic equations

12. Interpolation, Lagrange interpolation formula, differences and divided differences, Newton’s interpolation formula, numerical differentiation

13. Optimization methods, method of changing a single parameter, random walk method, grid search method (factorial design), rules for creating a regression model, experimental design,

14. Simplex method, variable-size simplex, expansion, contraction, optimization criteria

15. Monte Carlo methods - integration and simulation, pseudorandom number generators, Monte Carlo integration, Monte Carlo simulation.

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