LEADER 05369nam 2200613 a 450 001 9910139045803321 005 20230803021208.0 010 $a3-527-65343-0 010 $a3-527-65341-4 010 $a3-527-65344-9 035 $a(CKB)2550000001102581 035 $a(EBL)1315866 035 $a(OCoLC)853364768 035 $a(SSID)ssj0001034950 035 $a(PQKBManifestationID)11678536 035 $a(PQKBTitleCode)TC0001034950 035 $a(PQKBWorkID)11016387 035 $a(PQKB)10242448 035 $a(MiAaPQ)EBC1315866 035 $a(Au-PeEL)EBL1315866 035 $a(CaPaEBR)ebr10734635 035 $a(CaONFJC)MIL505064 035 $a(EXLCZ)992550000001102581 100 $a20130805d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aData analysis in high energy physics$b[electronic resource]$ea practical guide to statistical methods /$fedited by Olaf Behnke ... [et al.] 210 $aWeinheim an der Bergstrasse, Germany $cWiley-VCH Verlag GmbH$dc2013 215 $a1 online resource (441 p.) 300 $aDescription based upon print version of record. 311 $a3-527-41058-9 311 $a1-299-73813-3 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aData Analysis in High Energy Physics; Contents; Preface; List of Contributors; 1 Fundamental Concepts; 1.1 Introduction; 1.2 Probability Density Functions; 1.2.1 Expectation Values; 1.2.2 Moments; 1.2.3 Associated Functions; 1.3 Theoretical Distributions; 1.3.1 The Gaussian Distribution; 1.3.2 The Poisson Distribution; 1.3.3 The Binomial Distribution; 1.3.4 Other Distributions; 1.4 Probability; 1.4.1 Mathematical Definition of Probability; 1.4.2 Classical Definition of Probability; 1.4.3 Frequentist Definition of Probability; 1.4.4 Bayesian Definition of Probability 327 $a1.5 Inference and Measurement1.5.1 Likelihood; 1.5.2 Frequentist Inference; 1.5.3 Bayesian Inference; 1.6 Exercises; References; 2 Parameter Estimation; 2.1 Parameter Estimation in High Energy Physics: Introductory Words; 2.2 Parameter Estimation: Definition and Properties; 2.3 The Method of Maximum Likelihood; 2.3.1 Maximum-Likelihood Solution; 2.3.2 Properties of the Maximum-Likelihood Estimator; 2.3.3 Maximum Likelihood and Bayesian Statistics; 2.3.4 Variance of the Maximum-Likelihood Estimator; 2.3.5 Minimum-Variance Bound and Experiment Design; 2.4 The Method of Least Squares 327 $a2.4.1 Linear Least-Squares Method2.4.2 Non-linear Least-Squares Fits; 2.5 Maximum-Likelihood Fits:Unbinned, Binned, Standard and Extended Likelihood; 2.5.1 Unbinned Maximum-Likelihood Fits; 2.5.2 Extended Maximum Likelihood; 2.5.3 Binned Maximum-Likelihood Fits; 2.5.4 Least-Squares Fit to a Histogram; 2.5.5 Special Topic: Averaging Data with Inconsistencies; 2.6 Bayesian Parameter Estimation; 2.7 Exercises; References; 3 Hypothesis Testing; 3.1 Basic Concepts; 3.1.1 Statistical Hypotheses; 3.1.2 Test Statistic; 3.1.3 Critical Region; 3.1.4 Type I and Type II Errors 327 $a3.1.5 Summary: the Testing Process3.2 Choosing the Test Statistic; 3.3 Choice of the Critical Region; 3.4 Determining Test Statistic Distributions; 3.5 p-Values; 3.5.1 Significance Levels; 3.5.2 Inclusion of Systematic Uncertainties; 3.5.3 Combining Tests; 3.5.4 Look-Elsewhere Effect; 3.6 Inversion of Hypothesis Tests; 3.7 Bayesian Approach to Hypothesis Testing; 3.8 Goodness-of-Fit Tests; 3.8.1 Pearson's 2 Test; 3.8.2 Run Test; 3.8.3 2 Test with Unbinned Measurements; 3.8.4 Test Using the Maximum-Likelihood Estimate; 3.8.5 Kolmogorov-Smirnov Test; 3.8.6 Smirnov-Crame?r-von Mises Test 327 $a3.8.7 Two-Sample Tests3.9 Conclusion; 3.10 Exercises; References; 4 Interval Estimation; 4.1 Introduction; 4.2 Characterisation of Interval Constructions; 4.3 Frequentist Methods; 4.3.1 Neyman's Construction; 4.3.2 Test Inversion; 4.3.3 Pivoting; 4.3.4 Asymptotic Approximations; 4.3.5 Bootstrapping; 4.3.6 Nuisance Parameters; 4.4 Bayesian Methods; 4.4.1 Binomial Efficiencies; 4.4.2 Poisson Means; 4.5 Graphical Comparison of Interval Constructions; 4.6 The Role of Intervals in Search Procedures; 4.6.1 Coverage; 4.6.2 Sensitivity; 4.7 Final Remarks and Recommendations; 4.8 Exercises; References 327 $a5 Classification 330 $a This practical guide covers the essential tasks in statistical data analysis encountered in high energy physics and provides comprehensive advice for typical questions and problems. The basic methods for inferring results from data are presented as well as tools for advanced tasks such as improving the signal-to-background ratio, correcting detector effects, determining systematics and many others. Concrete applications are discussed in analysis walkthroughs. Each chapter is supplemented by numerous examples and exercises and by a list of literature and relevant links. The book targets a br 606 $aParticles (Nuclear physics)$xStatistical methods 615 0$aParticles (Nuclear physics)$xStatistical methods. 676 $a539.760285 701 $aBehnke$b Olaf$0938083 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139045803321 996 $aData analysis in high energy physics$92113263 997 $aUNINA