Statistics Education in Undergraduate Psychology: A Survey of UK Curricula

Abstract

Graduates from psychology programmes are likely to use data skills throughout their career, regardless of whether they continue into research. Statistical education in psychology programmes, however, emphasizes inferential statistical tests over a deep understanding of data and data skills, which can lead to the problematic use and interpretation of statistics. Indeed, widely-used statistical practices appear to undermine the quality of scientific research and mislead end-users of data. Several proposals have been made for how to improve these practices—with effective statistical education being one. With this in mind, we sought to document the statistical content currently taught to undergraduate psychology students in the UK. Contrary to our expectations, we found that only 19% of universities had publicly available curricula describing the statistical content taught in their undergraduate psychology programme. Of the curricula we obtained, most of them mentioned specific tests (ANOVAs, regression, correlation, t-tests, frequency tests, and rank tests) and about half mentioned probability and randomness, effect size, and statistical power, but few mentioned concepts such as confidence intervals, multiple comparisons, meta-analysis, replication, Bayesian statistics, frequentist statistics, and practical significance. These findings suggest that undergraduate psychology programmes may not emphasize statistical concepts (e.g., uncertainty) that are important for both everyday thinking and for effectively reporting and interpreting scientific research.