D. G. Altman and J. M. Bland, How to obtain the confidence interval from a P value, BMJ, vol.343, issue.aug08 1, p.2090, 2011.
DOI : 10.1136/bmj.d2090

J. S. Ancker, Y. Senathirajah, R. Kukafka, and J. B. Starren, Design Features of Graphs in Health Risk Communication: A Systematic Review, Journal of the American Medical Informatics Association, vol.13, issue.6, pp.608-618, 2006.
DOI : 10.1197/jamia.M2115

J. Boy, R. A. Rensink, E. Bertini, and J. Fekete, A Principled Way of Assessing Visualization Literacy, IEEE Transactions on Visualization and Computer Graphics, vol.20, issue.12, pp.1963-1972, 2014.
DOI : 10.1109/TVCG.2014.2346984

URL : https://hal.archives-ouvertes.fr/hal-01027582

S. K. Card, J. D. Mackinlay, and B. Shneiderman, Readings in information visualization: using vision to think, 1999.

R. N. Carney and J. R. Levin, Pictorial illustrations still improve students' learning from text, Educational Psychology Review, vol.14, issue.1, pp.5-26, 2002.
DOI : 10.1023/A:1013176309260

J. Chandler, P. Mueller, and G. Paolacci, Nonna¨?vetéNonna¨?veté among amazon mechanical turk workers: Consequences and solutions for behavioral researchers. Behavior research methods, pp.112-130, 2014.
DOI : 10.3758/s13428-013-0365-7

T. L. Childers, M. J. Houston, and S. E. Heckler, Measurement of Individual Differences in Visual versus Verbal Information Processing, Journal of Consumer Research, vol.12, issue.2, pp.125-134, 1985.
DOI : 10.1086/208501

J. Cohen, Statistical power analysis for the behavioral sciences lawrence earlbaum associates, pp.20-26, 1988.

M. Correll and M. Gleicher, Bad for data, good for the brain: Knowledgefirst axioms for visualization design, IEEE VIS 2014 (workshop DECI- SIVE), 2014.

G. Cumming, Understanding the new statistics: Effect sizes, confidence intervals, and meta-analysis, 2013.

G. Desanctis, COMPUTER GRAPHICS AS DECISION AIDS: DIRECTIONS FOR RESEARCH, Decision Sciences, vol.25, issue.1, pp.463-487, 1984.
DOI : 10.1177/107769906404100105

E. Dimara, A. Bezerianos, and P. Dragicevic, The Attraction Effect in Information Visualization, IEEE Transactions on Visualization and Computer Graphics, vol.23, issue.1, pp.471-480, 2017.
DOI : 10.1109/TVCG.2016.2598594

URL : https://hal.archives-ouvertes.fr/hal-01355750

P. Dragicevic, My technique is 20% faster: Problems with reports of speed improvements in HCI, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00739237

P. Dragicevic, Fair Statistical Communication in HCI, Modern Statistical Methods for HCI, pp.291-330, 2016.
DOI : 10.1007/978-3-319-26633-6_13

URL : https://hal.archives-ouvertes.fr/hal-01377894

K. Duklan and M. A. Martin, Communicating effectively with words, numbers and pictures: Drawing on experience. School of Finance and Applied Statistics, 2002.

K. Eriksson, The nonsense math effect, Judgment and decision making, vol.7, issue.6, p.746, 2012.

J. Fekete, J. Van-wijk, J. Stasko, and C. North, The Value of Information Visualization, Information visualization, pp.1-18, 2008.
DOI : 10.1007/978-3-540-70956-5_1

URL : https://hal.archives-ouvertes.fr/hal-00701741

G. D. Feliciano, R. D. Powers, and B. E. , The presentation of statistical information, Educational Technology Research and Development, vol.11, issue.3, pp.32-39, 1963.

G. Gigerenzer, W. Gaissmaier, E. Kurz-milcke, L. M. Schwartz, and S. Woloshin, Helping Doctors and Patients Make Sense of Health Statistics, Psychological Science in the Public Interest, vol.98, issue.2, pp.53-96, 2007.
DOI : 10.1016/j.cognition.2004.12.003

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.144.5595

D. J. Gillan, C. D. Wickens, J. G. Hollands, and C. M. Carswell, Guidelines for Presenting Quantitative Data in HFES Publications, Human Factors: The Journal of the Human Factors and Ergonomics Society, vol.32, issue.7, pp.28-41, 1998.
DOI : 10.1146/annurev.ps.32.020181.001203

P. Goffin, W. Willett, J. Fekete, and P. Isenberg, Exploring the Placement and Design of Word-Scale Visualizations, IEEE Transactions on Visualization and Computer Graphics, vol.20, issue.12, pp.2291-2300, 2014.
DOI : 10.1109/TVCG.2014.2346435

URL : https://hal.archives-ouvertes.fr/hal-01024278

G. L. Grace, Application of empirical methods to computer-based system design., Journal of Applied Psychology, vol.50, issue.6, p.442, 1966.
DOI : 10.1037/h0024049

S. Guri-rozenblit, Impact of diagrams on recalling sequential elements in expository texts Reading Psychology, An International Quarterly, vol.9, issue.2, pp.121-139, 1988.

J. Haard, M. D. Slater, and M. Long, Scientese and Ambiguous Citations in the Selling of Unproven Medical Treatments, Health Communication, vol.20, issue.1, pp.411-426, 2004.
DOI : 10.1509/jppm.19.1.132.16948

K. Hornbaek, S. S. Sander, J. A. Bargas-avila, and J. Simonsen, Is once enough?, Proceedings of the 32nd annual ACM conference on Human factors in computing systems, CHI '14, pp.3523-3532, 2014.
DOI : 10.1145/2556288.2557004

D. Huff, How to lie with statistics, 2010.

S. Jarvenpaa and G. W. Dickson, Graphics and managerial decision making: research-based guidelines, Communications of the ACM, vol.31, issue.6, pp.764-774, 1988.
DOI : 10.1145/62959.62971

O. N. Keene, The log transformation is special, Statistics in Medicine, vol.28, issue.8, pp.811-819, 1995.
DOI : 10.1007/978-1-4899-3242-6

D. Kelly, J. Jasperse, I. Westbrooke, S. Kim, and L. J. Lombardino, Designing science graphs for data analysis and presentation. Department of Conservation Technical Series Comparing graphs and text: Effects of complexity and task, Journal of Eye Movement Research, vol.32, issue.83, p.2015, 2005.

K. N. Kirby and D. Gerlanc, BootES: An R package for bootstrap confidence intervals on effect sizes. Behavior research methods, pp.905-927, 2013.
DOI : 10.3758/s13428-013-0330-5

J. H. Larkin and H. A. Simon, Why a Diagram is (Sometimes) Worth Ten Thousand Words, Cognitive Science, vol.1, issue.1, pp.65-100, 1987.
DOI : 10.1016/0004-3702(70)90004-4

M. Macdonald-ross, How numbers are shown, AV Communication Review, vol.25, issue.4, pp.359-409, 1977.

A. Mehta, Advertising Attitudes and Advertising Effectiveness, Journal of Advertising Research, vol.40, issue.3, pp.67-72, 2000.
DOI : 10.2501/JAR-40-3-67-72

L. Micallef, P. Dragicevic, and J. Fekete, Assessing the Effect of Visualizations on Bayesian Reasoning through Crowdsourcing, IEEE Transactions on Visualization and Computer Graphics, vol.18, issue.12, pp.2536-2545, 2012.
DOI : 10.1109/TVCG.2012.199

URL : https://hal.archives-ouvertes.fr/hal-00717503

J. Morgan and G. Michaelson, A comparative evaluation of tabular and graphical presentation styles for information retrieval search results, 2012.

T. Munzner, Visualization analysis and design, 2014.

B. Nyhan and J. Reifler, Does correcting myths about the flu vaccine work? An experimental evaluation of the effects of corrective information, Vaccine, vol.33, issue.3, pp.459-464, 2015.
DOI : 10.1016/j.vaccine.2014.11.017

A. V. Pandey, A. Manivannan, O. Nov, M. Satterthwaite, and E. Bertini, The Persuasive Power of Data Visualization, IEEE Transactions on Visualization and Computer Graphics, vol.20, issue.12, pp.2211-2220, 2014.
DOI : 10.1109/TVCG.2014.2346419

A. V. Pandey, K. Rall, M. L. Satterthwaite, O. Nov, and E. Bertini, How Deceptive are Deceptive Visualizations?, Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, CHI '15, pp.1469-1478, 2015.
DOI : 10.1177/0963662514549688

R. E. Rhodes, F. Rodriguez, and P. Shah, Explaining the alluring influence of neuroscience information on scientific reasoning., Journal of Experimental Psychology: Learning, Memory, and Cognition, vol.40, issue.5, p.1432, 2014.
DOI : 10.1037/a0036844

J. Sauro and J. R. Lewis, Average task times in usability tests, Proceedings of the 28th international conference on Human factors in computing systems, CHI '10, pp.2347-2350, 2010.
DOI : 10.1145/1753326.1753679

W. Schnotz and M. Bannert, Construction and interference in learning from multiple representation. Learning and instruction, pp.141-156, 2003.
DOI : 10.1016/s0959-4752(02)00017-8

M. Schonlau and E. Peters, Comprehension of Graphs and Tables Depend on the Task: Empirical Evidence from Two Web-Based Studies, Statistics, Politics, and Policy, vol.16, issue.2, p.2012
DOI : 10.1377/hlthaff.26.3.741

I. Spence, Visual psychophysics of simple graphical elements., Journal of Experimental Psychology: Human Perception and Performance, vol.16, issue.4, p.683, 1990.
DOI : 10.1037/0096-1523.16.4.683

J. Stahnke, M. Dörk, B. Müller, and A. Thom, Probing Projections: Interaction Techniques for Interpreting Arrangements and Errors of Dimensionality Reductions, IEEE Transactions on Visualization and Computer Graphics, vol.22, issue.1, pp.629-638, 2016.
DOI : 10.1109/TVCG.2015.2467717

D. L. Streiner, Breaking up is Hard to Do: The Heartbreak of Dichotomizing Continuous Data, The Canadian Journal of Psychiatry, vol.105, issue.3, pp.262-266, 2002.
DOI : 10.1037/0033-2909.105.1.156

A. Tal and B. Wansink, Blinded with science: Trivial graphs and formulas increase ad persuasiveness and belief in product efficacy, Public Understanding of Science, vol.52, issue.4, pp.117-125, 2016.
DOI : 10.1037/0022-3514.52.4.677

N. Tractinsky and J. Meyer, Chartjunk or Goldgraph? Effects of Presentation Objectives and Content Desirability on Information Presentation, MIS Quarterly, vol.23, issue.3, pp.397-420, 1999.
DOI : 10.2307/249469

E. R. Tufte, THE VISUAL DISPLAY OF QUANTITATIVE INFORMATION, Journal For Healthcare Quality, vol.7, issue.3, p.15, 1985.
DOI : 10.1097/01445442-198507000-00012

I. Vessey, Cognitive Fit: A Theory-Based Analysis of the Graphs Versus Tables Literature, Decision Sciences, vol.2, issue.1, pp.219-240, 1991.
DOI : 10.2307/3150659

I. Vessey, The effect of information presentation on decision making: A cost-benefit analysis, Information & Management, vol.27, issue.2, pp.103-119, 1994.
DOI : 10.1016/0378-7206(94)90010-8

J. N. Washburne, An experimental study of various graphic, tabular, and textual methods of presenting quantitative material., Journal of Educational Psychology, vol.18, issue.7, p.465, 1927.
DOI : 10.1037/h0070054

D. S. Weisberg, F. C. Keil, J. Goodstein, E. Rawson, and J. R. Gray, The Seductive Allure of Neuroscience Explanations, Journal of Cognitive Neuroscience, vol.92, issue.3, pp.470-477, 2008.
DOI : 10.1126/science.7455683

W. Wilcox, Numbers and the News: Graph, Table or Text?, Journalism Quarterly, vol.41, issue.1, pp.38-44, 1964.
DOI : 10.1177/107769906404100105

E. B. Wilson, Probable Inference, the Law of Succession, and Statistical Inference, Journal of the American Statistical Association, vol.22, issue.158, pp.209-212, 1927.
DOI : 10.1080/01621459.1927.10502953