V. Amrhein, S. Greenland, and B. Mcshane, Scientists rise up against statistical significance, Nature, vol.567, issue.7748, pp.305-307, 2019.

V. Amrhein, F. Korner-nievergelt, and T. Roth, The earth is flat (p>0.05) : Significance thresholds and the crisis of unreplicable research, PeerJ Preprints, vol.5, pp.2921-2923, 2017.

L. Besançon and P. Dragicevic, The significant difference between p-values and confidence intervals, Proc. IHM, vol.10, 2017.

L. Besançon and P. Dragicevic, The continued prevalence of dichotomous inferences at CHI, CHI '19 -Proceedings of CHI Conference on Human Factors in Computing Systems Extended Abstracts, 2019.

R. Calin-jageman and G. Cumming, The new statistics for better science : Ask how much, how uncertain, and what else is known, 2018.

G. Cumming, Understanding the new statistics : effect sizes, confidence intervals and meta-analysis, 2012.

P. Dragicevic, Fair statistical communication in HCI, Modern Statistical Methods for HCI, vol.13, pp.291-330, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01377894

P. Dragicevic, F. Chevalier, and S. Huot, Running an HCI experiment in multiple parallel universes, Extended Abstracts on Human Factors in Computing Systems, pp.607-618, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00976507

M. Kay, G. L. Nelson, and E. B. Hekler, Researcher-centered design of statistics : Why Bayesian statistics better fit the culture and incentives of HCI, Proceedings of the CHI 2016, pp.4521-4532, 2016.

D. Mccloskey and S. Ziliak, The Cult of Statistical Significance, 2008.

B. B. Mcshane and D. Gal, Statistical significance and the dichotomization of evidence, Journal of the American Statistical Association, vol.112, issue.519, pp.885-895, 2017.

R. L. Wasserstein, A. L. Schirm, and N. A. Lazar, Moving to a world beyond, The American Statistician, vol.73, issue.sup1, pp.1-19, 2019.