Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask
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Beschreibung
These notes describe how to average and fit numerical data that have been obtained either by simulation or measurement. Following an introduction on how to estimate various average values, they discuss how to determine error bars on those estimates, and how to proceed for combinations of measured values. Techniques for fitting data to a given set of models will be described in the second part of these notes. This primer equips readers to properly derive the results covered, presenting the content in a style suitable for a physics audience. It also includes scripts in python, perl and gnuplot for performing a number of tasks in data analysis and fitting, thereby providing readers with a useful reference guide.
These notes describe how to average and fit numerical data that have been obtained either by simulation or measurement. Following an introduction on how to estimate various average values, they discuss how to determine error bars on those estimates, and how to proceed for combinations of measured values. Techniques for fitting data to a given set of models will be described in the second part of these notes. This primer equips readers to properly derive the results covered, presenting the content in a style suitable for a physics audience. It also includes scripts in python, perl and gnuplot for performing a number of tasks in data analysis and fitting, thereby providing readers with a useful reference guide.
Includes supplementary material: sn.pub/extras
Autor*in
Peter Young
Themen in »Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask«
Analysis and Fitting of Experimental Data Data Analysis Textbook Distributions of Fitted Parameters Fitting of Correlated Data Maximum Likelihood versus Bayesian Approaches Perl and Gnuplot Scripts for Data Fitting Python Scripts for Data Analysis and Fitting Scripts for Data Analysis and Fitting Tasks