Get Data Analysis in High Energy Physics, A Practical Guide to PDF

By Olaf Behnke, Kevin Kroninger, Gregory Schott, Thomas Schorner-Sadenius

ISBN-10: 3527410589

ISBN-13: 9783527410583

ISBN-10: 3527653414

ISBN-13: 9783527653416

This useful consultant covers the basic initiatives in statistical info research encountered in excessive power physics and offers complete suggestion for standard questions and difficulties. the elemental tools for inferring effects from info are offered in addition to instruments for complicated projects equivalent to enhancing the signal-to-background ratio, correcting detector results, picking out systematics etc. Concrete purposes are mentioned in research walkthroughs. each one bankruptcy is supplemented via a variety of examples and workouts and by way of an inventory of literature and suitable hyperlinks. The publication goals a wide readership in any respect profession degrees - from scholars to senior researchers. An accompanying web site presents extra algorithms in addition to updated info and links.

* unfastened ideas guide on hand for academics at www.wiley-vch.de/supplements/

Content:
Chapter 1 basic recommendations (pages 1–26): Roger Barlow
Chapter 2 Parameter Estimation (pages 27–73): Dr. Olaf Behnke and Lorenzo Moneta
Chapter three speculation checking out (pages 75–105): Dr. Gregory Schott
Chapter four period Estimation (pages 107–151): Luc Demortier
Chapter five category (pages 153–186): Helge Voss
Chapter 6 Unfolding (pages 187–225): Volker Blobel
Chapter 7 limited matches (pages 227–262): Benno List
Chapter eight the right way to take care of Systematic Uncertainties (pages 263–296): Rainer Wanke
Chapter nine conception Uncertainties (pages 297–328): Markus Diehl
Chapter 10 Statistical equipment standard in excessive power Physics (pages 329–356): Carsten Hensel and Dr. Kevin Kroninger
Chapter eleven research Walk?Throughs (pages 357–379): Aart Heijboer and Ivo van Vulpen
Chapter 12 purposes in Astronomy (pages 381–407): Harrison B. Prosper

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Additional resources for Data Analysis in High Energy Physics, A Practical Guide to Statistical Methods

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Trans. R. , 53, 370. 11 Jeffreys, H. (1966) Theory of Probability, Oxford University Press. , and Sun, D. (2009) The formal definition of reference priors. Ann. , 37, 905. 1 Parameter Estimation in High Energy Physics: Introductory Words The estimation of parameters from observed distributions, a process also called fitting, is one of the fundamental data analysis tasks in experimental high energy physics; it is applied in almost every step of a measurement. In collider experiments, for instance, a typical goal is to identify new particles which are produced in hard collisions of two incident beam particles.

4 Probability We use probability every day, in both our work as physicists and our everyday lives. Sometimes this is a matter of precise calculation, when we buy an insurance policy or decide whether to publish a result, sometimes it is more intuitive, as when we decide to take an umbrella to work in the morning. But although we are familiar with the concept of probability, on closer inspection it turns out that there are subtleties. When we get into technicalities there turn out to be different definitions of the concept which are not always compatible.

3b). The exact log-likelihood functions, obtained from QN x i /θ /θ , are depicted as solid curves. The dashed lines show L(xI θ ) D iD1 e parabolas obtained from a Taylor expansion of the log-likelihood function around its maximum at θO . These parabolas represent local Gaussian approximations of the likelihood function. 5. However, for a similar drop, the Gaussian approximation works already much better for the case of eight events. This illustrates the convergence of the likelihood function to a Gaussian distribution with increasing number of events, which is a consequence of the central limit theorem.

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Data Analysis in High Energy Physics, A Practical Guide to Statistical Methods by Olaf Behnke, Kevin Kroninger, Gregory Schott, Thomas Schorner-Sadenius


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