Monte Carlo Data Analysis:

The Monte Carlo analysis as implemented in UltraScan is a method that allows you to evaluate statistical parameters of your fit. You start the Monte Carlo analysis by clicking on the Monte Carlo buttons in a nonlinear least squares fitting module for the various experimental analyses. The Monte Carlo Analysis Window will appear. This function is used to control the Monte Carlo modeling of the fitting parameters. If you are not familiar with Monte Carlo analysis, you are encouraged to consult a good statistics text book, or review the mini-tutorial from UltraScan.

The Monte Carlo Simulation program allows you to generate the equivalent of multiple experimental observations by simulating experimental noise using a random number generator. Each simulated observation can then be refitted and provide a new parameter vector of estimated best fit solutions. The collection of parameters can then be used to derive statistical measurements that allow you to assign a confidence to the obtained parameter value.

Explanation of Fields:

www contact: Borries Demeler

This document is part of the UltraScan Software Documentation distribution.
Copyright © notice.

The latest version of this document can always be found at:

Last modified on January 12, 2003