ror.org/03c4mmv16
Abstracts
Résumé
Les statistiques sont une matière notoirement difficile à enseigner aux étudiants des sciences humaines. L’anxiété statistique, une forme d’anxiété bien documentée chez ces étudiants, est présente dès le début du cours et explique donc une partie des difficultés rencontrées par ces étudiants. Cependant, nous croyons que l’anxiété statistique est la conséquence plutôt que la source de ces difficultés. Pour enclencher une discussion qui, à terme, pourrait bonifier la façon d’enseigner les statistiques dans les sciences humaines, nous examinons ici trois causes qui pourraient expliquer cet anxiété. D’une part, les humains ont très peu d’intuition du hasard (comme le montrent les études sur les jeux d’argent dans lesquels des conceptions erronées sont dévoilées), et donc, les notions de distribution et d’échantillonnage restent des concepts opaques pour plusieurs. De plus, certains concepts statistiques reposent sur des raisonnements « méta-statistiques » dans lesquels il faut concevoir des statistiques sur des statistiques. Finalement, la notion de prise de décision dans un contexte où l’information est partielle et incertaine est souvent mal comprise. Dans ce texte, nous précisons ces trois difficultés et suggérons des recommandations pour en amoindrir les conséquences. Cependant, les pistes présentées ici nécessitent d’être validées par des études formelles; ce texte se veut avant tout un catalyseur de discussions visant l’amélioration de l’état de nos classes de méthodes quantitatives.
Mots-clés :
- Éducation aux statistiques,
- fondements conceptuels,
- hasard,
- échantillonnage,
- méta-statistique
Abstract
Statistics is a content matter notoriously difficult to teach to students of the social sciences. Statistical anxiety, a well-documented form of anxiety, is present from the beginning of the course and explains in part the learning difficulties experienced by these students. However, we believe that statistics anxiety is a consequence and not the source of these difficulties. To initiate a discussion on how statistical teaching could be improved in the social sciences, we consider herein three causes that might explain that anxiety. To initiate a discussion which could lead to improvements in the way statistics is taught, we examine herein three possible causes of this anxiety. First, human beings have very limited intuitions of randomness (as can be seen from erroneous conceptions from compulsive players) and consequently, distributions and sampling remains opaque concepts for many. Second, some statistical concepts are truly “meta-statistical” concepts in which one must conceive of statistics onto statistics. Finally, procedures for decision taking in contexts where information is limited and inaccurate are often poorly understood. In this text, we detail these three conceptual difficulties and propose recommendations to weaken their consequences. The propositions presented here still need to be validated with formal studies; this text hope to be a catalyst of discussions aiming at improving the teaching of quantitative methods and statistics.
Keywords:
- Statistics education,
- concepts grounding,
- randomness,
- sampling,
- meta-statistic
Download the article in PDF to read it. Download
Appendices
Remerciements
Nous tenons à remercier vivement les nombreux collègues qui nous ont donnés leurs commentaires sur ce texte, en particulier André Achim, Dominic Beaulieu-Prévost, Sébastien Béland, Michael Cantinotti, Éric Frenette, Léon Harvey, et Daniel Lalande. Les discussions tenues aux colloques Méthodes Quantitatives et Sciences Humaines au fil des années ont aussi été très utiles; je souligne en particulier les apports de Rachad Antonius, Marcos Balbinotti, Nathalie Loye, Walter Marcontoni et Sophie Parent. Je tiens aussi à remercier certains de mes étudiants, dont Alexandra Turgeon et Alexandre Lafrenière. Cette recherche est appuyée en partie par des bourses de l’Ontario Graduate Scholarship et du Conseil pour la Recherche en Sciences Naturelles et en Génie accordée au second auteur et par une subvention du Conseil pour la Recherche en Sciences Naturelles et en Génie accordée au premier auteur.
Bibliographie
- Allen, K. (2006). The statistics concept inventory: Developpement and analysis of a cognitive assesment instrument in statistics (Technical report series No. unpublished dissertation). Norman, OK: University of Oklahoma.10.1016/S0191-8869(02)00076-4 Google Scholar Search this bibliographic reference on Google Scholar
- American Statistical Association with Aliaga, M., Cobb, G., Cuff, C., Garfield, J., Gould, R., Lock, R., Moore, T… Witmer, J. (2005). Guidelines for Assessment and Instruction in Statistics Education [GAISE] College Report. Alexandria, VA: American Statistical Association.10.1016/j.socec.2013.05.009 Google Scholar Search this bibliographic reference on Google Scholar
- Baloglu, M. (2003). Individual differences in statistics anxiety among college students. Personality and Individual Differences, 34, 855-865. doi: 10.1016/S0191-8869(02)00076-410.1016/S0191-8869(02)00076-4 Google Scholar Search this bibliographic reference on Google Scholar
- Becchetti, L., Castriota, S., Corrado, L. et Giachin Ricca, E. (2013). Beyond the Joneses: Inter-country income comparisons and happiness. The Journal of Socio-Economics, 45, 187-195.10.1016/j.socec.2013.05.009 Google Scholar Search this bibliographic reference on Google Scholar
- Béland, S., Cousineau, D. et Loye, N. (2016). Les dix commandements du nouvel homo statisticus. McGill journal of education/Revue des sciences de l’éducation de McGill. 51, 947-960.
10.7202/1038612ar
Google Scholar
Search this bibliographic reference on Google Scholar
- Belmont, L. et Marolla, F. A. (1973) Birth order, family size, and intelligence. Science, 182, 1096-1101.10.1126/science.182.4117.1096 Google Scholar Search this bibliographic reference on Google Scholar
- Benson, J. (1989). Structural components of statistical test anxiety in adults: An exploratory model. Journal of Experimental Education, 57, 247-261. doi: 10.1080/00220973.1989.1080650910.1080/00220973.1989.10806509 Google Scholar Search this bibliographic reference on Google Scholar
- Blanché, R. (1967) La science actuelle et le rationalisme. Paris, France : Presse Universitaire de France 10.1037/0003-066X.49.12.997 Google Scholar Search this bibliographic reference on Google Scholar
- Boole, G. (1854). An Investigation of the Laws of Thought on Which are Founded the Mathematical Theories of Logic and Probabilities. Macmillan. Reprinted with corrections, Dover Publications, New York, NY, 1958 and reissued by Cambridge University Press, 200910.5962/bhl.title.29413 Google Scholar Search this bibliographic reference on Google Scholar
- Cantinotti , M., Lalande , D., Ferlatte, M.-A. et Cousineau, D. (2017) Validation de la version francophone du Questionnaire d’anxiété statistique (SAS-F-24). Revue canadienne des sciences du comportement, 49, 133–142.10.1037/cbs0000074 Google Scholar Search this bibliographic reference on Google Scholar
- Chanquoy, L., Tricot, A. et Sweller, J. (2007). La charge cognitive : théorie et applications. Paris, France : Armand Colin.10.20982/tqmp.10.2.p077 Google Scholar Search this bibliographic reference on Google Scholar
- Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49, 997-1003. doi: 10.1037/0003-066X.49.12.99710.1037/0003-066X.49.12.997 Google Scholar Search this bibliographic reference on Google Scholar
- Cohen, J. (1969). Statistical power analysis for the behavioral sciences. San Diego, CA: Academic Press.10.1111/j.1467-9639.2005.00205.x Google Scholar Search this bibliographic reference on Google Scholar
- Cohen, J. (1990). Things I have learned (So far). American psychologist, 45, 1304-1312. doi: 10.1037/0003-066X.45.12.130410.1037/0003-066X.45.12.1304 Google Scholar Search this bibliographic reference on Google Scholar
- Coulter, X. (1995). A new way of teaching statistics. Journal of Educational Statistics, 24, 181-187. doi: 10.2190/K906-0M2X-CGTE-7XGV10.2190/K906-0M2X-CGTE-7XGV Google Scholar Search this bibliographic reference on Google Scholar
- Cousineau, D. (2009). Panorama des statistiques pour les sciences humaines. Bruxelles, Belgique : De Boeck, 445 p. 10.20982/tqmp.11.3.p189 Google Scholar Search this bibliographic reference on Google Scholar
- Cousineau, D. (2014). Restoring confidence in psychological science findings: A call for direct replication studies. The Quantitative Methods for Psychology, 10, 77-79. doi: 10.20982/tqmp.10.2.p07710.20982/tqmp.10.2.p077 Google Scholar Search this bibliographic reference on Google Scholar
- Cousineau, D. et Allan, T. A. (2015). Likelihood and its use in Parameter Estimation and Model Comparison. Mesures et Évaluation en Éducation, 37, 63-98. doi: 10.7202/1036328ar10.7202/1036328ar
Google Scholar
Search this bibliographic reference on Google Scholar
- Dunn, P. K. (2005). We can still learn about probability by rolling dice and tossing coins. Teaching Statistics, 27, 37-41. doi: 10.1111/j.1467-9639.2005.00205.x10.1111/j.1467-9639.2005.00205.x Google Scholar Search this bibliographic reference on Google Scholar
- Finney, S.J. et Schraw, G. (2003). Self-efficacy beliefs in college statistics courses. Contemporary Educational Psychology, 28, 161-186. doi: 10.1016/S0361-476X(02)00015-210.1016/S0361-476X(02)00015-2 Google Scholar Search this bibliographic reference on Google Scholar
- Fisher, R. A. (1925) Statistical methods for research workers. Edinburgh, Écosse: Oliver and Boyd.10.20982/tqmp.12.2.p138 Google Scholar Search this bibliographic reference on Google Scholar
- Furnham, A. et Chamorro-Premuzic, T. (2004). Personality and intelligence as predictors of statistics examination grades. Personality and Individual Differences, 37, 943-955. doi: 10.1016/j.paid.2003.10.016 10.1016/j.paid.2003.10.016 Google Scholar Search this bibliographic reference on Google Scholar
- George, A. C. et Robitzsch, A. (2015). Cognitive diagnosis models in R: A didactic. The Quantitative Methods for Psychology, 11, 189-205. doi: 10.20982/tqmp.11.3.p18910.20982/tqmp.11.3.p189 Google Scholar Search this bibliographic reference on Google Scholar
- Haar, M. (1998-2015). RANDOM.ORG: True Random Number Service. Retrieved October 7th, 2016, from https://www.random.org/10.1080/00207590244000250 Google Scholar Search this bibliographic reference on Google Scholar
- Hair, P. et Hampson, S. E. (2006). The role of impulsivity in predicting maladaptative behaviour among female students. Personality and Individual Differences, 40, 943-952. doi: 10.1016/j.paid.2005.10.00210.1016/j.paid.2005.10.002 Google Scholar Search this bibliographic reference on Google Scholar
- Halloun, H. A. et Hestenes, D. (1985). Common sense concepts about motion. American Journal of Physics, 53, 1056-1065. doi: 10.1119/1.1403110.1119/1.14031 Google Scholar Search this bibliographic reference on Google Scholar
- Harding, B., Cousineau, D. (2014). GRD: An SPSS extension command for generating random data. The Quantitative Methods for Psychology, 10, 80-94. doi: 10.20982/tqmp.10.2.p08010.20982/tqmp.10.2.p080 Google Scholar Search this bibliographic reference on Google Scholar
- Harding, B. et Cousineau, D. (2015). GRD 2.0: An extended SPSS extension command for generating random data. The Quantitative Methods for Psychology, 11, 127-138. doi: 10.20982/tqmp.11.3.p12710.20982/tqmp.11.3.p127 Google Scholar Search this bibliographic reference on Google Scholar
- Harding, B. et Cousineau, D. (2016). GSD: An SPSS extension command for sub-sampling and bootstrapping datasets. The Quantitative Methods for Psychology, 12, 145-153. doi: 10.20982/tqmp.12.2.p13810.20982/tqmp.12.2.p138 Google Scholar Search this bibliographic reference on Google Scholar
- Harding, B., Tremblay, C. et Cousineau, D. (2014). Standard errors: A review and evaluation of standard error estimators using Monte Carlo simulations. The Quantitative Methods for Psychology, 10, 107-123. doi: 10.20982/tqmp. 10.2.p10710.1080/00220973.1995.9943816 Google Scholar Search this bibliographic reference on Google Scholar
- Harding, B., Tremblay, C., Cousineau, D. (2015) The Standard Error of the Pearson Skew. The Quantitative Methods for Psychology. 11, 32-36. doi: 10.20982/tqmp.11.1.p03210.20982/tqmp.11.1.p032 Google Scholar Search this bibliographic reference on Google Scholar
- Hoijtink, H. (2012) Informative hypotheses: Theory and applications for behavioral and social scientists. London, UK: Chapman et Hall/CRC.10.1037/h0042040 Google Scholar Search this bibliographic reference on Google Scholar
- Konold, C. (1995). Issues in assessing conceptual understanding in probability and statistics. Journal of Statistics Education, 3, 1-12. 10.1080/10691898.1995.11910479 Google Scholar Search this bibliographic reference on Google Scholar
- Küchenhoff, H. (2008). Coin Tossing and Spinning – Useful Classroom Experiments for Teaching Statistics, dans Shalabh, Heumann, C. (Dir.). Recent Advances in Linear Models and Related Areas: Essays in Honour of Helge Toutenburg (pp. 417-426). Heidelberg: Psysica-Verlag HD.10.3758/BF03194105 Google Scholar Search this bibliographic reference on Google Scholar
- Lane, D. (n.d.) Online statistics education: A multimedia course of study. http://Onlinestatbook.com (last retrieved 22/06/2016).10.1080/00031305.2016.1154108 Google Scholar Search this bibliographic reference on Google Scholar
- Lecoutre, M.-P., Poitevineau, J. et Lecoutre, B. (2003) Even statisticians are not immune to miinterpretations of null hypothesis significance tests. International Journal of Psychology, 38, 37-45.10.1080/00207590244000250 Google Scholar Search this bibliographic reference on Google Scholar
- Loftus, G. R. (1996). Psychology will be a much better science when we change the way we analyse data. Current Directions in Psychological Science, 5, 161-171. doi: 10.1111/1467-8721.ep1151237610.1111/1467-8721.ep11512376 Google Scholar Search this bibliographic reference on Google Scholar
- Marmolejo-Ramos, F. et Matsunaga, M. (2009) Getting the most from your curves: Exploring and reporting data using informative graphical techniques. Tutorials in Quantitative Methods for Psychology, 5, 40-50. doi: 10.20982/tqmp.05.2.p04010.20982/tqmp.05.2.p040 Google Scholar Search this bibliographic reference on Google Scholar
- Marson, S. M. (2007). Three empirical strategies for teaching statistics. Journal of Teaching in Social Work, 27, 199-213. doi: 10.1300/J067v27n03_1310.1300/J067v27n03_13 Google Scholar Search this bibliographic reference on Google Scholar
- Neyman, J. et Pearson, E. S. (1933). On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 231, 289–337. .10.1098/rsta.1933.0009 Google Scholar Search this bibliographic reference on Google Scholar
- Nickerson, R. S. (2002) The production and perception of randomness. Psychological Review, 109, 330-357. doi: 10.1037/0033-295X.109.2.330 10.1037/0033-295X.109.2.330 Google Scholar Search this bibliographic reference on Google Scholar
- Onwuegbuzie, A. .J. et Daley, C. E. (1999). Perfectionism and statistics anxiety. Personality and Individual Differences, 26, 1089-1102. doi: 0.1016/S0191-8869(98)00214-1Google Scholar Search this bibliographic reference on Google Scholar
- Onwuegbuzie, A. J. et Seaman, M. A. (1995). The effect of time constraints and statistics test anxiety on test performance in a statistics course. Journal of Experimental Education, 63, 115-124. doi: 10.1080/00220973.1995.994381610.1080/00220973.1995.9943816 Google Scholar Search this bibliographic reference on Google Scholar
- Pashler, H. et Wagenmakers, E.-J. (2012) Editor’s introduction to the special section on replicability in psychological science: A crisis of confidence? Perspectives on Psychological Science, 7, 528-530. doi: 10.1177/174569161246525310.1177/1745691612465253 Google Scholar Search this bibliographic reference on Google Scholar
- Rossman, A.J. et Chance, B.L. (n.d.) Rossman/Chance Applet Collection. Page consultée le 7 Octobre 2016, depuis http://www.rossmanchance.com/applets/index.html.Google Scholar Search this bibliographic reference on Google Scholar
- Rozeboom, W. W. (1960). The fallacy of the null-hypothesis significance test. Psychological Bulletin, 57, 416-428. doi: 10.1037/h004204010.1037/h0042040 Google Scholar Search this bibliographic reference on Google Scholar
- Stuart, M. (1995). Changing the teaching of statistics. The Statistician, 44, 45-54. doi: 10.2307/234861510.2307/2348615 Google Scholar Search this bibliographic reference on Google Scholar
- T. Groulx, J. et Cousineau, D. (2016). Ivote: A system for televoting. The Quantitative Methods for Psychology, 13, 57-64. 10.1016/S0191-8869(98)00214-1 Google Scholar Search this bibliographic reference on Google Scholar
- Vigil-Colet, A., Lorenzo-Seva, U. et Condon, L. (2008). Development and validation of the Statistical Anxiety Scale. Psicothema, 20, 174-180. Google Scholar Search this bibliographic reference on Google Scholar
- Wagenmakers, E.-J. (2007). A practical solution to the pervasive problems of p values. Psychonomic Bulletin and Review, 14, 779-804. doi: 10.3758/BF0319410510.3758/BF03194105 Google Scholar Search this bibliographic reference on Google Scholar
- Wasserstein, R. L. et Lazar, N. A. (2016). ASA’s statement on statistical significance and p-values. The American Statistician, version en libre accès, 1-6. doi: 10.1080/00031305.2016.115410810.1080/00031305.2016.1154108 Google Scholar Search this bibliographic reference on Google Scholar
- Wiens, S. et Nilsson, M. E. (sous presse) A tutorial on contrast analyses in factorial designs: From NHST to confidence intervals and beyond. Educational and Psychological Measurement.Google Scholar Search this bibliographic reference on Google Scholar
- Yilmaz, M. R. (1996). The challenge of teaching statistics to non-specialists. Journal of Statistics Education, 4, 1-9.10.1080/10691898.1996.11910504 Google Scholar Search this bibliographic reference on Google Scholar