Abstract
In experimental particle physics as well as in many other fields, it has become increasingly important to analyze data in a manner that extracts the maximum information and takes into account all of the known uncertainties. This article reviews the most important statistical methods used to carry out this task. It begins with an overview of probability, as this forms the basis for quantifying uncertainty. The statistical methods considered include the general framework of statistical tests and parameter estimation, including methods for constructing intervals such as upper limits. Both frequentist and Bayesian approaches are described.
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Notes
- 1.
This chapter is largely excerpted and adapted from the reviews on Probability and Statistics in the Review of Particle Physics by the Particle Data Group Nakamura et al. (2010).
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Cowan, G. (2012). Statistics. 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_5
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