Uso interativo de planilha eletrônica para o ensino de Estatística: O caso do valor de p.<br>Interactive use of spreadsheets to teach statistics: The case for the p value

Autores/as

DOI:

https://doi.org/10.23925/1983-3156.2018v21i2p187-201

Palabras clave:

Valor de p, Planilha Eletrônica, Inferência, Simulação

Resumen

O objetivo deste artigo foi avaliar os efeitos do uso de planilha eletrônica interativa para simular eventos na aprendizagem do conceito estatístico inferencial do valor de p. O presente estudo possui uma abordagem metodológica quantitativa e qualitativa, baseada na descoberta guiada, em que os alunos recebem uma série de atividades que os levam a um objetivo predeterminado. Os resultados obtidos neste estudo demonstram que o procedimento adotado pode ser um aliado no ensino da inferência, e que a simulação torna as atividades mais ativas permitindo que os alunos descubram os próprios princípios, tornando o aprendizado mais efetivo.

The aim of this article was to evaluate the effects of the use of interactive spreadsheets to simulate events for the learning of the inferential statistical concept to determine the p value, which represents the probability of the effect observed between the treatments being due to the natural variation of the samples, and not to the factors being investigated. The present study has developed a quantitative and qualitative methodological approach based on guided discovery in which students are offered a series of activities that leads them to a predetermined objective. The results obtained show that the procedure chosen can be helpful for teaching inference and indicate that simulation makes activities more dynamic, allowing students to discover the principles themselves, which makes learning more effective.

Métricas

Cargando métricas ...

Biografía del autor/a

Fernando Frei, UNESP

Fernando Frei é bacharel em Estatística pela Universidade Federal de São Carlos – UFSCar, possui mestrado e doutorado em Saúde Pública pela USP de São Paulo. Docente de Estatística na Universidade Estadual Paulista – UNESP. Professor credenciado no Programa de Pós-Graduação em Biociências da FCLAssis - UNESP

Citas

ANDERSON-COOK, C. M.; DORAI-RAJ, S. Making the Concepts of Power and Sample Size Relevant and Accessible to Students in Introductory Statistics Courses using Applets. Journal of Statistics Education v. 11, n. 3, p. 1-12, 2003.

AQUILONIUS, B. C., BRENNER, M. E. Students’ reasoning about p-values. Statistics Education Research Journal, v. 14, n. 2, p. 7-27, 2015.

BADENES-RIBERA, L.; FRIAS-NAVARRO, D.; IOTTI, B.; BONILLA-CAMPOS, A.; LONGOBARDI, C. Misconceptions of the p-value among Chilean and Italian Academic. Psychologists, v. 7, p. 1-7, 2016.

BATANERO, C.; DIAZ, C. Methodological and Didactical Controversies around Statistical Inference (2006). Proceedings of 38th Conference of the French Statistical Conference. Actes du 36iémes Journées de la Societé Française de Statistique. Paris: Societé Française de Statistique. Disponível em <http://www.ugr.es/~batanero/pages/ARTICULOS/SFE.pdf>. Acesso em: 10 fevereiro de 2018.

BIAU, D. J.; JOLLES, B. M. PORCHER, R. P Value and the Theory of Hypothesis Testing: An Explanation for New Researchers, Clin Orthop Relat Res, v. 468, p. 885-892, 2010.

CAÑADAS, G. R.; BATANERO, C.; DIAZ, C.; ROA, R. Psychology students’ understanding of the chi-squared test. Statistique et Enseignement, v. 3, n. 1, p. 3-8, 2012.

CHANDRAKANTHA, L. Simulation using excel data tables in teaching introductory statistics. Journal of Computing Sciences in Colleges, v. 29, p. 29-34, 2014.

COHEN, J. The earth is round (p < 0.05). American Psychologist, v. 49, n. 12, p. 997-1003, 1994.

CUMMING, G. (2010). Understanding, teaching and using p values. In A. Rossman & B. Chance (Eds.), ICOTS-10 Proceedings. Disponível em https://iase-web.org/documents/papers/icots8/ICOTS8_8J4_CUMMING.pdf. Acesso em: 10 fevereiro de 2018.

CURRAN-EVERETT, D. Explorations in statistics: hypothesis tests and P values. Adv Physiol Educ, v. 33, p. 81-86, 2009.

DE JONG, T.; VAN JOOLIGEN, W. Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, v. 68, n. 2, p. 179-201, 1998.

DELMAS, R.; GARFIELD, J.; CHANCE, B. A model of classroom research in action: Developing simulation activities to improve students’ statistical reasoning. Journal of Statistics Education, v. 7, n. 3, 1999. Disponível em: < https://ww2.amstat.org/publications/jse/secure/v7n3/delmas.cfm>. Acesso em: 10 de janeiro de 2018.

DUFFY, S. Random Numbers Demonstrate the Frequency of Type I Errors: Three Spreadsheets for Class Instruction. Journal of Statistics Education, v. 18, n. 2, p. 1-16, 2010.

ERICKSON, T. Using simulation to learn about inference. Proceedings of the Seventh International Conference on Teaching Statistics, ICOTS-7, 2006. Disponível em: https://www.researchgate.net/profile/Tim_Erickson2/publication/248282382_USING_SIMULATION_TO_LEARN_ABOUT_INFERENCE/links/5694828c08ae425c6896488d/USING-SIMULATION-TO-LEARN-ABOUT-INFERENCE.pdf. Acesso em: 18 de janeiro de 2018.

FALK, R. Misconceptions of statistical significance. Journal of Structural Learning, v. 9, p. 83-96, 1986.

GOODMAN S. A dirty dozen: twelve p-value misconceptions. Semin Hematol, v. 45, n. 3, p. 135-40, 2008.

GOODMAN, S. Commentary: The P-value, devalued. International Journal of Epidemiology, v. 32, p. 699-702, 2003.

GREENLAND, S.; SENN, S. J.; ROTHMAN, K. J.; CARLIN, J. B.; POOLE, C.; GOODMAN, S. N.; ALTMAN; D. G. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations, Eur J Epidemiol, v. 31, p. 337-350, 2016.

HALLER, H.; KRAUSS, S. Misinterpretations of significance: A problem students share with their teachers? Methods of Psychological Research, v. 7, n. 1, p. 1-20, 2002.

HATTIE, J.; TIMPERLAY, H. The power of feedback. Review of Educational Research, v. 77, n. 1, p. 81-112, 2007.

HUBBARD, R.; LINDSAY, R. M. Why P values are not a useful measure of evidence in statistical significance testing. Theory Psychol, v. 18, p. 69-88, 2008.

HUNT, N.; MASHHOUDY, H. Charts in Excel – A Series Matter. Teaching Statistics, v. 26, n. 2, p. 49-53, 2004.

JAMIE. D. M. Using Computer Simulation Methods to Teach Statistics: A Review of the Literature, Journal of Statistics Education, v. 10, n. 1, p. 1-20, 2002.

KLAHR, D.; NIGAM, M. The equivalence of learning paths in early science instruction. Psychological Science, v. 15, n. 10, p. 661-667, 2004.

LANE, D. M.; PERES, S. C. Interactive simulations in the teaching of statistics: Promise and Pitfalls. Proceedings of the Seventh Annual Meeting of the International Conference on the Teaching of Statistics, Salvador, Brazil, 2006. Disponível em: <http://www.ruf.rice.edu/~lane/papers/interactive-simulations.pdf>. Acesso em: 10 de fevereiro de 2018.

LANG, J. M.; ROTHMAN, K.; CANN, C. I. That confounded P-value. Epidemiology, v. 9, p. 7-8, 1998.

LE D. Bringing Data to Life into an Introductory Statistics Course with GAPMINDER. Teaching Statistics, v. 35, n. 3, p. 114-122, 2013.

MARTIN, D.; COLLEGE, D. A. Spreadsheet Tool for Learning the Multiple Regression F-test, t-tests, and Multicollinearity. Journal of Statistics Education, v. 16, n. 3, 2008. Disponível em: <https://www.tandfonline.com/doi/pdf/10.1080/10691898.2008.11889573?needAccess=true>. Acesso em: 15 de fevereiro de 2018.

MILLS, J. Using computer simulation methods to teach statistics: A review of the literature. Journal of Statistics Education, v. 10, n. 1, p. 1-10, 2002.

MURPHY, S. J. (2009). The power of visual learning in secondary mathematics education. Pearson Education Inc. Disponível em <https://assets.pearsonschool.com/asset_mgr/legacy/200916/MatMon092291HS2011StuMur_LR_20702_1.pdf>. Acesso em: 09 de janeiro de 2018.

NUZZO, R. Scientific method: Statistical errors. Nature, v. 506, p. 150 –152, 2004.

QUINTELA-DEL-RÍO, A.; FRANCISCO-FERNÁNDEZ, M. Excel Templates: A Helpful Tool for Teaching Statistics. The American Statistician, V. 71, p. 317- 325, 2014.

SALEHI, M. Using MS Excel in Teaching Design of Experiment. International Journal of Education and Learning Systems, v. 1, p. 93 – 98, 2016.

SCHMIDT, F. L.; HUNTER, J. E. What If There Were No Significance Tests? Eight common but false objections to the discontinuation of significance testing in analysis of research data. HARLOW L., MULAIK S. e STEIGER J. (Eds.) New York. Routledge, p. 37-64, 1997.

SEBASTIANI, R. G.; VIALI, L. Teste de Hipóteses: uma análise dos erros cometidos por alunos de engenharia. Bolema, v. 24, n. 40, p. 835-854, 2011.

SOTOS, A. E. C.; VANHOOF, S.; NOORTGATE, W. V.; ONGHENA, P. Students’ misconceptions of statistical inference: A review of the empirical evidence from research on statistics education. Educational Research Review, v. 2, p. 98-113, 2007.

STERNE, J. A. C. Teaching hypothesis tests – time for significant change? Statistics in Medicine, v. 21, p. 985-994, 2002.

VALLECILLOS, A. Empirical evidence about understanding of the level of significance concept in hypotheses testing by university students. Themes in Education, v. 3, n. 2, p. 183-198, 2002.

ZACHAROPOULOU, H. Two Learning Activities for a Large Introductory Statistics Class. Journal of Statistics Education, v. 14, n. 1, p. 1-10, 2006.

ZIEFFLER, A.; GARFIELD, J.; DELMAS, R.; READING, C. A framework to support research on informal inferential reasoning. Statistics Education Research Journal, v. 7, n. 2, p. 40-58, 2008.

Publicado

2019-09-02

Cómo citar

FREI, F. Uso interativo de planilha eletrônica para o ensino de Estatística: O caso do valor de p.&lt;br&gt;Interactive use of spreadsheets to teach statistics: The case for the p value. Educação Matemática Pesquisa, São Paulo, v. 21, n. 2, 2019. DOI: 10.23925/1983-3156.2018v21i2p187-201. Disponível em: https://revistas.pucsp.br/index.php/emp/article/view/37784. Acesso em: 21 nov. 2024.

Número

Sección

Artigos