大葉大學圖書館 |

Statistical methods for data analysis in particle physics[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	539.720727
書名/作者:	Statistical methods for data analysis in particle physics/ by Luca Lista.
作者:	Lista, Luca.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	xix, 172 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Nuclear physics - Statistical methods.
標題:	Physics.
標題:	Elementary Particles, Quantum Field Theory.
標題:	Measurement Science and Instrumentation.
標題:	Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
ISBN:	9783319201764
ISBN:	9783319201757
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-20176-4

Statistical methods for data analysis in particle physics[electronic resource] /
Lista, Luca.

Statistical methods for data analysis in particle physics[electronic resource] /by Luca Lista. - Cham :Springer International Publishing :2016. - xix, 172 p. :ill. (some col.), digital ;24 cm. - Lecture notes in physics,v.9090075-8450 ;. - Lecture notes in physics ;v.830..

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.

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.

ISBN: 9783319201764

Standard No.: 10.1007/978-3-319-20176-4doiSubjects--Topical Terms:

651752
Nuclear physics
--Statistical methods.

LC Class. No.: QC793.47.S83

Dewey Class. No.: 539.720727

Statistical methods for data analysis in particle physics[electronic resource] /
LDR:02219nam a2200325 a 4500 001 454351
003 DE-He213
005 20160712111418.0
006 m d
007 cr nn 008maaau
008 161227s2016 gw s 0 eng d
020 $a 9783319201764 $q (electronic bk.)
020 $a 9783319201757 $q (paper)
024 7 $a 10.1007/978-3-319-20176-4 $2 doi
035 $a 978-3-319-20176-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QC793.47.S83
072 7 $a PHQ $2 bicssc
072 7 $a SCI051000 $2 bisacsh
082 0 4 $a 539.720727 $2 23
090 $a QC793.47.S83 $b L773 2016
100 1 $a Lista, Luca. $3 651751
245 1 0 $a Statistical methods for data analysis in particle physics $h [electronic resource] / $c by Luca Lista.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xix, 172 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in physics, $x 0075-8450 ; $v 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 Nuclear physics $x Statistical methods. $3 651752
650 1 4 $a Physics. $3 171863
650 2 4 $a Elementary Particles, Quantum Field Theory. $3 464245
650 2 4 $a Measurement Science and Instrumentation. $3 465064
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 464764
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
830 0 $a Lecture notes in physics ; $v v.830. $3 464212
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-20176-4
950 $a Physics and Astronomy (Springer-11651)