One Parameter Chi-squared Analysis

Autor: Keith Zengel, Carey Witkov
Rok vydání: 2019
Předmět:
Zdroj: Chi-Squared Data Analysis and Model Testing for Beginners
Popis: The chi-squared method for parameter estimation and model testing is developed for the one-parameter case of a line with a slope but no intercept. Curve fitting is motivated, and several methods for curve fitting are introduced. The chi-squared method is shown to be the optimal curve fitting method whenever Gaussian distributed measurement uncertainties and a model are present. The central limit theorem, which assures Gaussian distributed measurement uncertainties for a wide range of physical experiments, is introduced. End-of-chapter problems are included (with solutions in an appendix).
Databáze: OpenAIRE