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02522nam a22004815i 4500 |
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978-3-319-19051-8 |
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DE-He213 |
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20151204152817.0 |
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cr nn 008mamaa |
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150519s2015 gw | s |||| 0|eng d |
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|a 9783319190518
|9 978-3-319-19051-8
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|a 10.1007/978-3-319-19051-8
|2 doi
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|a SCI068000
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|a 530.8
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|a Young, Peter.
|e author.
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|a Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask
|h [electronic resource] /
|c by Peter Young.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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|a X, 85 p. 15 illus., 11 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
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|a text file
|b PDF
|2 rda
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|a SpringerBriefs in Physics,
|x 2191-5423
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|a Introduction -- Averages and Error Bars -- Fitting Data to a Model -- Appendices -- References.
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|a 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.
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|a Physics.
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|a Physical measurements.
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|a Measurement.
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|a Statistics.
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|a Physics.
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|a Measurement Science and Instrumentation.
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|a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
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| 650 |
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|a Numerical and Computational Physics.
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| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783319190501
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| 830 |
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|a SpringerBriefs in Physics,
|x 2191-5423
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|u http://dx.doi.org/10.1007/978-3-319-19051-8
|z Full Text via HEAL-Link
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|a ZDB-2-PHA
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|a Physics and Astronomy (Springer-11651)
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