|
|
|
|
LEADER |
03087nam a22005415i 4500 |
001 |
978-3-319-20176-4 |
003 |
DE-He213 |
005 |
20151204164011.0 |
007 |
cr nn 008mamaa |
008 |
150724s2016 gw | s |||| 0|eng d |
020 |
|
|
|a 9783319201764
|9 978-3-319-20176-4
|
024 |
7 |
|
|a 10.1007/978-3-319-20176-4
|2 doi
|
040 |
|
|
|d GrThAP
|
050 |
|
4 |
|a QC793-793.5
|
050 |
|
4 |
|a QC174.45-174.52
|
072 |
|
7 |
|a PHQ
|2 bicssc
|
072 |
|
7 |
|a SCI051000
|2 bisacsh
|
082 |
0 |
4 |
|a 539.72
|2 23
|
100 |
1 |
|
|a Lista, Luca.
|e author.
|
245 |
1 |
0 |
|a Statistical Methods for Data Analysis in Particle Physics
|h [electronic resource] /
|c by Luca Lista.
|
250 |
|
|
|a 1st ed. 2016.
|
264 |
|
1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2016.
|
300 |
|
|
|a XIX, 172 p. 63 illus., 59 illus. in color.
|b online resource.
|
336 |
|
|
|a text
|b txt
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
347 |
|
|
|a text file
|b PDF
|2 rda
|
490 |
1 |
|
|a Lecture Notes in Physics,
|x 0075-8450 ;
|v 909
|
505 |
0 |
|
|a Preface -- Probability theory -- Probability Distribution Functions -- Bayesian approach to probability -- Random numbers and Monte Carlo Methods -- Parameter estimate -- Confidence intervals -- Hypothesis tests -- Upper Limits -- Bibliography.
|
520 |
|
|
|a This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data.
|
650 |
|
0 |
|a Physics.
|
650 |
|
0 |
|a Elementary particles (Physics).
|
650 |
|
0 |
|a Quantum field theory.
|
650 |
|
0 |
|a Physical measurements.
|
650 |
|
0 |
|a Measurement.
|
650 |
|
0 |
|a Statistics.
|
650 |
1 |
4 |
|a Physics.
|
650 |
2 |
4 |
|a Elementary Particles, Quantum Field Theory.
|
650 |
2 |
4 |
|a Measurement Science and Instrumentation.
|
650 |
2 |
4 |
|a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
|
710 |
2 |
|
|a SpringerLink (Online service)
|
773 |
0 |
|
|t Springer eBooks
|
776 |
0 |
8 |
|i Printed edition:
|z 9783319201757
|
830 |
|
0 |
|a Lecture Notes in Physics,
|x 0075-8450 ;
|v 909
|
856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-319-20176-4
|z Full Text via HEAL-Link
|
912 |
|
|
|a ZDB-2-PHA
|
912 |
|
|
|a ZDB-2-LNP
|
950 |
|
|
|a Physics and Astronomy (Springer-11651)
|