Bibliography

15
https://it.wikipedia.org/wiki/Auditel .

16
Marco Lillo, Covid: sono stato infettato, ma l’ho scoperto da solo, Il Fatto Quotidiano, 8 April 2020,
https://www.ilfattoquotidiano.it/in-edicola/articoli/2020/04/08/covid-sono-stato-infettato-ma-lho-scoperto-da-solo/5763424/.

17
https://en.wikipedia.org/wiki/Immunoglobulin_M .

18
https://en.wikipedia.org/wiki/Immunoglobulin_G .

19
G. D'Agostini, Probability, Propensity and Probability of Propensities (and of Probabilities), AIP Conference Proceedings 1853, 030001 (2017),
https://arxiv.org/abs/1612.05292.

20
G. D'Agostini, A defense of Columbo (and of the use of Bayesian inference in forensics): A multilevel introduction to probabilistic reasoning,
https://arxiv.org/abs/1003.2086 .

21
G. D'Agostini and A. Esposito, Così è...probabilmente - Il saggio, l'ingenuo e la signorina Bayes, Ilmiolibro, 2016, (Italian only), https://ilmiolibro.kataweb.it/libro/storia-e-filosofia/102643/cos-probabilmente/.

22
G. D'Agostini, N. Cifani and A. Gilardi, Talking about Probability, Inference and Decisions. Part 1: The Witches of Bayes (Italian only), Progetto Alice, Vol. XIX, nr. 55 pp. 73-134, 2018, https://arxiv.org/abs/1802.10432.

23
S. L. Frasier, Coronavirus Antibody Tests Have a Mathematical Pitfall, Scientific American, July 1, 2020, https://www.scientificamerican.com/article/coronavirus-antibody-tests-have-a-mathematical-pitfall/ .

24
M. Plummer, JAGS: A Program for Analysis of Bayesian Graphical Models Using Gibbs Sampling, Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), March 20–22, Vienna, Austria. ISSN 1609-395X, http://mcmc-jags.sourceforge.net/ .

25
R Core Team (2018), R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
https://www.R-project.org/ .

26
M. Plummer, rjags: Bayesian Graphical Models using MCMC.
R package version 4-10, https://CRAN.R-project.org/package=rjags .

27
P.S. Laplace, Mémoire sur la probabilité des causes par les événements”, Mémoire de l'Académie royale des Sciences de Paris (Savants étrangers), Tome VI, p. 621, 1774, https://gallica.bnf.fr/ark:/12148/bpt6k77596b/f32 .

28
https://en.wikipedia.org/wiki/Sensitivity_and_specificity .

29
International Organization for Standardization (ISO), Guide to the expression of uncertainty in measurement, Geneva, Switzerland, 1993.

30
Nicholas M. Coquillard, Note, Negligent HIV Testing and False-Positive Plaintiffs: Pardoning the Traditional Prerequisites for Emotional Distress Recovery, 43 Clev. St. L. Rev. 655 (1995).

31
N. Fenton et al., Bayes and the Law, Ann. Rev. Stat. Appl., Vol. 3, pp. 51-77 (2016), doi:10.1146/annurev-statistics-041715-033428,
https://www.researchgate.net/publication/298425265_Bayes_and_the_Law.

32
J. J. Koehler, Forensic Fallacies and a famous Judge, Jurimetrics, vol. 54, no. 3, 2014, pp. 211-219. JSTOR, https://www.jstor.org/stable/24395599. Accessed 26 Aug. 2020.

33
A. Esposito, Debunking some myths about biometric authentication,
https://arxiv.org/abs/1203.0333 .

34
G. D'Agostini, The Gauss' Bayes Factor,
https://arxiv.org/abs/2003.10878 .

35
Bayes, Thomas and Price, Richard An Essay towards solving a Problem in the Doctrine of Chance. By the late Rev. Mr. Bayes, communicated by Mr. Price, in a letter to John Canton, A.M.F.R.S., Philosophical Transactions of the Royal Society of London. 53: 370–418, (1763), <<7418>>https://doi.org/10.1098

1
M. Bognar, Probability distributions,
https://play.google.com/store/apps/details?id=com.mbognar.probdist,
https://apps.apple.com/us/app/probability-distributions/id889106396 .

2
G. D'Agostini, Bayesian Inference in Processing Experimental Data: Principles and Basic Applications, Rept.Prog.Phys. 66 (2003) 1383-1420,
https://arxiv.org/abs/physics/0304102 .

3
G. D'Agostini, Bayesian Reasoning in Data Analysis. A critical Introduction, World Scientific, 2003.

4
https://en.wikipedia.org/wiki/Hypergeometric_distribution .

5
C. Andrieu et al., An introduction to MCMC for Machine Learning, Machine Learning 50 5-43 (2003), https://doi.org/10.1023/A:1020281327116 .

6
D. Lunn et al., The BUGS project: Evolution, critique and future directions, Statistics in Medicine 28 3049-3067 (2008), https://doi.org/10.1002/sim.3680 .

7
The BUGS Project, http://www.mrc-bsu.cam.ac.uk/software/bugs/ .

8
http://www.openbugs.net/w/Examples .

9
C.F. Gauss, Theoria motus corporum coelestium in sectionibus conicis solem ambientum, Hamburg 1809, https://archive.org/details/bub_gb_ORUOAAAAQAAJ .

10
P. Astone and G. D'Agostini, Inferring the intensity of Poisson processes at the limit of the detector sensitivity (with a case study on gravitational wave burst search), CERN-EP/99-126, https://arxiv.org/abs/hep-ex/9909047 .

11
G. D'Agostini and G. Degrassi, Constraints on the Higgs boson mass from direct searches and precision measurements, Eur. Phys. J. C10 (1999) 633, https://arxiv.org/abs/hep-ph/9902226 .

12
S. Gariazzo, Constraining power of open likelihoods, made prior-independent, https://arxiv.org/abs/1910.06646.

13
G. D'Agostini, Sceptical combination of experimental results using JAGS/rjags with application to the tex2html_wrap_inline$K_±$ mass determination,
https://arxiv.org/abs/2001.03466v1 .

14
M. Becker and S. Klössner, PearsonDS: Pearson Distribution System,
https://cran.r-project.org/web/packages/PearsonDS/index.html .