The following books and articles are suggested as prior reading to help provide some background information on statistical issues in particle physics analyses. We do not expect participants to read them all.
- "Statistical Data Analysis" Glen Cowan
- L. Lyons, "Statistics for Nuclear and Particle Physicists", (Cambridge
University Press, New York, 1986). - F. James, "Statistical Methods in Experimental Physics", 2nd ed., (World Scientific, Singapore, 2007)
- O. Behnke, K. Kroeninger, G. Schott and T. Schoerner-Sadenius, "A Practical Guide to Statistical Methods" (Wiley-VCH 2013)
- L. Lista, "Statistical Methods for Data Analysis in Particle Physics", Springer, 2017
- Particle Data Group review on Statistics, Glen Cowan
(There are also sections on Probability Theory and on Monte Carlo Techniques.) This is a short summary, and not intended to be a tutorial.
In the following we provide a list of some recent Statistics Schools with many nice pedagogical lecture/tutorial materials, from beginners to advanced levels:
- 1st Pan-European Advanced School of Statistics in High Energy Physics
- 5th Machine Learning school in High Energy Physics (organised by Yandex School of Data Analysis)
- INFN Statistics School 2019
- 1st Terascale School of Machine Learning
- Terascale Statistics School 2018
