Statistical training in Brazilian graduate programs: an analysis of the courses offered
DOI:
https://doi.org/10.1590/S1678-4634202349249290Keywords:
Graduate Studies, Courses, StatisticsAbstract
Statistics is one of the foundations of science, and its teaching in graduate programs has a direct influence on shaping the next generation of researchers. This study provides a general overview of statistics-related courses in stricto sensu graduate programs in Brazil, based on the analysis of the syllabi of 176,823 courses, of which 12,552 contained content related to statistics. Among the findings, it was observed that only a few programs have mandatory courses specifically related to statistics. The higher the concept of the graduate program according to Capes evaluation, the greater the average number of statistics-related courses offered. However, this relationship is not evident in the mandatory courses. Regarding the content of the courses, they can be divided into two main groups: one with a theoretical foundation in probability and statistics, and another focused on applications and the use of tools. There is a small third group of courses offered in the English language. Finally, the availability of courses related to advanced techniques (such as Machine Learning) is much smaller compared to the offering of statistics-related courses, and it is mainly concentrated in Engineering and Exact and Earth Sciences programs.
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AIKEN, Leona S. et al. Graduate training in statistics, methodology, and measurement in psychology: A survey of PhD programs in North America. American Psychologist, Washington, DC, v. 45, n. 6, p. 721, 1990.
ANDERSON, Britta L.; WILLIAMS, Sterling; SCHULKIN, Jay. Statistical literacy of obstetrics-gynecology residents. Journal of Graduate Medical Education, Chicago, v. 5, n. 2, p. 272-275, 2013.
BLEI, David M.; NG, Andrew Y.; JORDAN, Michael I. Latent dirichlet allocation. Journal of Machine Learning Research, Massachusetts, v. 3, p. 993-1022, Jan. 2003.
BRASIL. Ministério da Educação. Portaria n. 389, de 23 de março de 2017. Dispõe sobre o mestrado e doutorado profissional no âmbito da pós-graduação stricto sensu. Brasília, DF: Ministério da Educação, 2017. Disponível em: http://cad.capes.gov.br/ato-administrativo-detalhar?idAtoAdmElastic=241#anchor Acesso em: 18 jul. 2022.
» http://cad.capes.gov.br/ato-administrativo-detalhar?idAtoAdmElastic=241#anchor
BZDOK, Danilo; ALTMAN, Naomi; KRZYWINSKI, Martin. Points of significance: statistics versus machine learning. Nature Methods, London, v. 15, p. 233-234, 2018.
CAMPOS, Celso Ribeiro et al. Educação estatística no contexto da educação crítica. Bolema, Rio Claro, v. 24, n. 39, p. 473-494, 2011.
CAMPOS, Geraldo Maia. Estatística prática para docentes e pós-graduandos. Faculdade de Odontologia de Ribeirão Preto, Ribeirão Preto, v. 35, 2001. Disponível em: www.forp.usp.br/restauradora/gmc/gmc_livro/gmc_livro_prefacio.html Acesso em: 01 fev. 2021.
CAPES. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior. Plataforma Sucupira, Brasília, DF, 2020. Disponível em: https://sucupira.capes.gov.br/sucupira/ Acesso em: 01 ago. 2020.
» https://sucupira.capes.gov.br/sucupira/
COCHRAN, William. Graduate training in statistics. The American Mathematical Monthly, Washington, DC, v. 53, n. 4, p. 193-199, 1946.
DELMAS, Robert C. Statistical literacy, reasoning, and thinking: A commentary. Journal of Statistics Education, Alexandria, v. 10, n. 2, 2002.
DURRANI, Naureen; TARIQ, Vicki N. The role of numeracy skills in graduate employability. Education+Training, London, v. 54, n. 5, p. 419-434, 2012.
FISHER, Ronald A. Mathematics of a lady tasting tea. The world of mathematics, New York, v. 3, n. part. 8, p. 1514-1521, 1956.
FONG, Geoffrey T.; KRANTZ, David H.; NISBETT, Richard E. The effects of statistical training on thinking about everyday problems. Cognitive psychology, Massachusetts, v. 18, n. 3, p. 253-292, 1986.
FONTICHIARO, Kirstin; OEHRLI, Jo Angela. Why data literacy matters. Knowledge Quest, Chicago, v. 44, n. 5, p. 21-27, 2016.
GAL, Iddo. Adults’ statistical literacy: meanings, components, responsibilities. International Statistical Review, Haia, v. 70, n. 1, p. 1-25, 2002.
GÉRON, Aurélien. Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: concepts, tools, and techniques to build intelligent systems. Sebastopol: O’Reilly Media, 2019.
GONULAL, Talip; LOEWEN, Shawn; PLONSKY, Luke. The development of statistical literacy in applied linguistics graduate students. ITL-International Journal of Applied Linguistics, Louvaina, v. 168, n. 1, p. 4-32, 2017.
GOULD, Robert. Data literacy is statistical literacy. Statistics Education Research Journal, Haia, v. 16, n. 1, p. 22-25, 2017.
HANNIGAN, Ailish; HEGARTY, Avril C.; MCGRATH, Deirdre. Attitudes towards statistics of graduate entry medical students: the role of prior learning experiences. BMC Medical Education, Cham, v. 14, n. 1, p. 1-7, 2014.
HARRAWAY, John A.; BARKER, Richard J. Statistics in the workplace: a survey of use by recent graduates with higher degrees. Statistics Education Research Journal, Haia, v. 4, n. 2, p. 43-58, 2005.
KULSHRESTHA, Ria. A beginner’s guide to Latent Dirichlet Allocation (LDA). Toronto: [s. n.], 2019. Disponível em: https://towardsdatascience.com/latent-dirichlet-allocation-lda-9d1cd064ffa2 Acesso em: 14 jul. 2022.
» https://towardsdatascience.com/latent-dirichlet-allocation-lda-9d1cd064ffa2
LEHMAN, Darrin R.; LEMPERT, Richard O.; NISBETT, Richard E. The effects of graduate training on reasoning: Formal discipline and thinking about everyday-life events. American Psychologist, Washington, DC, v. 43, n. 6, p. 431, 1988.
MAGNUSSON, William E. Estatística, delineamento amostral e projetos integrados: a falta de coerência no ensino e na prática. Revista Brasileira de Ecologia, Rio Claro, v. 1, p. 37-40, 1999.
MURTONEN, Mari. University students’ research orientations: do negative attitudes exist toward quantitative methods?. Scandinavian Journal of Educational Research, Oxfordshire, v. 49, n. 3, p. 263-280, 2005.
MUSTAFA, R. Yilmaz. The challenge of teaching statistics to non-specialists. Journal of Statistics Education, Alexandria, v. 4, n. 1, 1996.
OLIVEIRA, Rosana Halinski de. NAE-Núcleo de Assessoria Estatística: assessorias e cursos de curta Duração/2017. Salão de Extensão, 18., Porto Alegre, 2017. Caderno de resumos. Porto Alegre: UFRGS/PROREXT, 2017. Disponível em: https://www.lume.ufrgs.br/bitstream/handle/10183/185634/Resumo_34917.pdf?sequence=1 Acesso em: 15 jan. 2021.
» https://www.lume.ufrgs.br/bitstream/handle/10183/185634/Resumo_34917.pdf?sequence=1
ONWUEGBUZIE, Anthony J.; LEECH, Nancy L. On becoming a pragmatic researcher: the importance of combining quantitative and qualitative research methodologies. International Journal of Social Research Methodology, London, v. 8, n. 5, p. 375-387, 2005.
PAN, Wei; TANG, Mei. Examining the effectiveness of innovative instructional methods on reducing statistics anxiety for graduate students in the social sciences. Journal of Instructional Psychology, Milwaukee, v. 31, n. 2, 2004.
POPPER, Karl R. A lógica da pesquisa científica. São Paulo: Cultrix, 2004.
REDFERN, Nick. Film studies and statistical literacy. Media Education Research Journal, Bournemouth, v. 4, n. 1, p. 58-71, 2013.
RESTON, Enriqueta. Models of student learning in graduate statistics education: Towards statistical literacy and research competence. Ackland, 2007. SESSION OF THE INTERNATIONAL STATISTICAL INSTITUTE (ISI 2007), 56., Lisboa, 2007. Proceedings […]: 22-29 ago. 2007. Lisboa: ISI, 2007. Disponível em: https://iase-web.org/documents/papers/isi56/CPM81_Reston.pdf?1402524979 Acesso em: 01 fev. 2021.
» https://iase-web.org/documents/papers/isi56/CPM81_Reston.pdf?1402524979
RUTHERFORD, Malcolm. The USDA Graduate School: government training in statistics and economics, 1921-1945. Journal of the History of Economic Thought, Cambridge, v. 33, n. 4, p. 419-447, 2011.
SCHIELD, Milo. Statistical literacy and mathematical thinking. In: INTERNATIONAL CONGRESS ON MATHEMATICS EDUCATION, 9., 2000, Tokyo. Proceedings […]. Tokyo: [s. n.], 2000. Disponível em: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=6fe66aaea876e3678ecf6aadecb8cd37bf033c36 Acesso em: 02 fev. 2021.
SCHUFF, David. Data science for all: a university-wide course in data literacy. In: DEOKAR, Amit et al. Analytics and data science. Cham: Springer, 2018. p. 281-297.
SNEE, Ronald D. What’s missing in statistical education?. The American Statistician, Alexandria, v. 47, n. 2, p. 149-154, 1993.
SYED, Shaheen; SPRUIT, Marco. Full-text or abstract? examining topic coherence scores using latent dirichlet allocation. In: IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS (DSAA), 2017, Tokyo. Anais […]. Tokyo: IEEE, 2017. p. 165-174.
TREWIN, Dennis. Improving statistical literacy: the respective roles of schools and the National Statistical Offices. In: BIENNIAL CONFERENCE OF THE AUSTRALIAN ASSOCIATION OF MATHEMATICS TEACHERS, 28., 2005, Adelaide. Anais […]. Adelaide: Australian Association of Mathematics Teachers, 2005. p. 11-19.
VARIAN, Hal R. Big data: New tricks for econometrics. Journal of Economic Perspectives, Nashville, v. 28, n. 2, p. 3-28, 2014.
WALLMAN, Katherine K. Enhancing statistical literacy: enriching our society. Journal of the American Statistical Association, Alexandria, v. 88, n. 421, p. 1-8, 1993.
ZEIDNER, Moshe. Statistics and mathematics anxiety in social science students: some interesting parallels. British Journal of Educational Psychology, London, v. 61, n. 3, p. 319-328, 1991.
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