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This is a session of Topic 5: Statistics education and the wider society             Full topic list

(Monday 3rd, 16:00-18:00)

Statistics in the social sciences - Psychology, Sociology



These are exciting times for statistical practice in the Social Sciences! There are many lively debates among researchers about which techniques are best for designing research, drawing conclusions from data, and communicating results. How should we respond to the telling criticisms of null hypothesis significance testing? Will confidence intervals be more effective for promoting understanding of research findings? How widely can meta-analysis be used to answer society’s big questions? Should robust methods, or Bayesian techniques, or resampling methods be more widely used in the Social Sciences? What graphical representations make findings vivid, and easily appreciated by policy makers and the public?

This session will discuss the consequences for statistics education of these debates. How should the statistics curriculum and teaching methods be developed to best serve students in the Social Sciences? How can researchers be most effectively supported to understand and choose less familiar techniques that will be most useful for their research?


PaperTitlePresenter(s) / Author(s)
5E1A non-standard approach to teaching an introductory Statistics course to social science studentsPatrick Murphy (Ireland)
5E2Intensive use of factorial correspondence analysis for text mining: application with Statistical education publicationsAnnie Morin (France)
5E3Assessing Psychology students’ difficulties with conditional probability and Bayesian reasoningCarmen Díaz (Spain)
Inmaculada de la Fuente
5E4Should Psychology abandon p values and teach CIs instead? Evidence-based reforms in Statistics educationFiona Fidler (Australia)