Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask
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 va...
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Springer
2016
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oai:scholar.dlu.edu.vn:DLU123456789-598162023-11-11T06:52:26Z Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask Young, Peter Numerical analysis Maximal subgroups Mathematical physics 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. 2016-03-15T01:33:36Z 2016-03-15T01:33:36Z 2015 Book 978-3-319-19051-8 978-3-319-19050-1 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/59816 en application/pdf Springer |
| institution |
Thư viện Trường Đại học Đà Lạt |
| collection |
Thư viện số |
| language |
English |
| topic |
Numerical analysis Maximal subgroups Mathematical physics |
| spellingShingle |
Numerical analysis Maximal subgroups Mathematical physics Young, Peter Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask |
| description |
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. |
| format |
Book |
| author |
Young, Peter |
| author_facet |
Young, Peter |
| author_sort |
Young, Peter |
| title |
Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask |
| title_short |
Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask |
| title_full |
Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask |
| title_fullStr |
Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask |
| title_full_unstemmed |
Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask |
| title_sort |
everything you wanted to know about data analysis and fitting but were afraid to ask |
| publisher |
Springer |
| publishDate |
2016 |
| url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/59816 |
| _version_ |
1819828846337196032 |