找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask; Peter Young Book 2015 The Author(s) 2015 Analysis an

[复制链接]
查看: 6747|回复: 35
发表于 2025-3-21 16:13:32 | 显示全部楼层 |阅读模式
书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask
编辑Peter Young
视频video
概述Includes supplementary material:
丛书名称SpringerBriefs in Physics
图书封面Titlebook: Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask;  Peter Young Book 2015 The Author(s) 2015 Analysis an
描述.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..
出版日期Book 2015
关键词Analysis and Fitting of Experimental Data; Data Analysis Textbook; Distributions of Fitted Parameters;
版次1
doihttps://doi.org/10.1007/978-3-319-19051-8
isbn_softcover978-3-319-19050-1
isbn_ebook978-3-319-19051-8Series ISSN 2191-5423 Series E-ISSN 2191-5431
issn_series 2191-5423
copyrightThe Author(s) 2015
The information of publication is updating

书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask影响因子(影响力)




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask影响因子(影响力)学科排名




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask网络公开度




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask网络公开度学科排名




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask被引频次




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask被引频次学科排名




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask年度引用




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask年度引用学科排名




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask读者反馈




书目名称Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask读者反馈学科排名




单选投票, 共有 0 人参与投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用户组没有投票权限
发表于 2025-3-21 20:30:34 | 显示全部楼层
Peter YoungIncludes supplementary material:
发表于 2025-3-22 03:16:06 | 显示全部楼层
发表于 2025-3-22 04:59:45 | 显示全部楼层
发表于 2025-3-22 12:33:44 | 显示全部楼层
https://doi.org/10.1007/978-1-4020-8786-8These notes describe how to average and fit numerical data that you have obtained, presumably by some simulation.
发表于 2025-3-22 15:44:36 | 显示全部楼层
Bin Cao,Bulbul Ahmed,Haluk BeyenalA reference for the material in this subsection is the book by Taylor [.]. Suppose we have a set of data from a simulation, ., which we shall refer to as a . of data.
发表于 2025-3-22 19:43:52 | 显示全部楼层
发表于 2025-3-22 23:22:43 | 显示全部楼层
发表于 2025-3-23 03:47:30 | 显示全部楼层
Averages and Error Bars,A reference for the material in this subsection is the book by Taylor [.]. Suppose we have a set of data from a simulation, ., which we shall refer to as a . of data.
发表于 2025-3-23 06:28:57 | 显示全部楼层
Fitting Data to a Model,A good reference for the material in this section is Chap. 15 of Numerical Recipes [.]. Frequently we are given a set of data points ., with corresponding error bars, ., through which we would like to fit to a smooth function .. The function could be straight line (the simplest case), a higher order polynomial, or a more complicated function.
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-17 19:26
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表