Abstract
The basic goal of data analysis is to establish a link between a set of measurements, in the form of electronically stored data using some format, and a theoretical model, which is intended to describe the phenomena at the origin of these measurements and usually is summarized by a set of equations with some parameters. The key elements of data analysis are data abstraction and data reduction. Abstraction means that the original set of raw measurements, e.g., a collection of electronic pulses induced by a particle passing through a detector, is converted (“reconstructed”) into physical quantities and properties which can be assigned to the particle, such as its momentum or its energy. Typically, this process is accompanied by data reduction, i.e., the overall data volume is reduced when going from the original set of measurements to a compilation of reconstructed physical quantities.
In this chapter, I will describe the steps involved in order to achieve the above-mentioned data abstraction and reduction in the case of Particle Physics experiments. Examples will be given for measurements carried out at e + e − as well as hadron colliders. The basic concepts behind reconstruction algorithms, such as track finding in tracking detectors and energy measurements in calorimeters, will be discussed, along with higher-level algorithms such as particle-jet reconstruction. Finally, the typical software and computing environment of large collider experiments will be described, which is necessary in order to achieve the outlined goals of data analysis.
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References
Berthold MR, Hand DJ (2003) Intelligent data analysis, 2nd edn. Springer, Berlin
Blazey GC, Flaugher BL (1999) Ann Rev Nucl Part Sci 49:633–685
Brandt S (1998) Data analysis: statistical and computational methods for scientists and engineers, 3rd edn. Springer, Berlin
Cowan G (1998) Statistical data analysis. Clarendon, Oxford
Dissertori G, Knowles IG, Schmelling M (2003) Quantum chromodynamics: high energy experiments and theory, 2nd edn. Clarendon, Oxford
Elliott J, Marsh C (2009) Exploring data: an introduction to data analysis for social scientists, 2nd edn. Polity, Oxford
Fishman G (1996) Monte Carlo: concepts, algorithms and applications. Springer, New York
Frühwirth R, Regler M, Bock RK, Grote H, Notz D (2000) Data analysis techniques for high-energy physics, 2nd edn. Cambridge University Press, Cambridge
Griffiths D (2008) Introduction to elementary particles, 2nd edn. Wiley-VCH, Weinheim
Koop G (2009) Analysis of economic data, 3rd edn. Wiley, New York
Lazar NA (2009) The statistical analysis of functional MRI data. Springer, New York
Lyman Ott R, Longnecker MT (2008) An introduction to statistical methods and data analysis, 6th edn. Duxbury, Belmont
Nisbet R, Elder IV J, Miner G (1997) Handbook of statistical analysis and data mining applications. Springer, New York
Perkins DH (2000) Introduction to high energy physics, 4th edn. Cambridge University Press, Cambridge
Quinn GP, Keough MJ (2002) Experimental design and data analysis for biologists. Cambridge University Press, Cambridge
Roff DA (2006) Introduction to computer-intensive methods of data analysis in biology. Cambridge University Press, Cambridge
Salam GP, preprint arXiv:0906.1833 [hep-ph], http://arxiv.org/abs/0906.1833
Sivia D, Skilling J (2006) Data analysis: A Bayesian tutorial, 2nd edn. Oxford University Press, Oxford
Wigmans R (2003) Calorimetry: energy measurement in particle physics. Clarendon, Oxford
Zaidi H (2006) Quantitative analysis in nuclear medicine imaging. Springer, New York
Zupan B, Keravnou E, Lavrac N (1997) Intelligent data analysis in medicine and pharmacology. Springer, Berlin
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Dissertori, G. (2012). Data Analysis. In: Grupen, C., Buvat, I. (eds) Handbook of Particle Detection and Imaging. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13271-1_4
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DOI: https://doi.org/10.1007/978-3-642-13271-1_4
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