Dr Vicky Gorton, Dr Kevin Ralston, June 2020
For many students Statistics = Anxiety. This anxiety is often characterised as limiting students’ engagement with statistics and impacting on their performance on quantitative methods courses at university. The relationships between age, gender and statistics anxiety are some of the most examined in the research literature. A survey of these findings might lead us to reformulate the Statistics = Anxiety equation to read: Statistics + Women = >Anxiety, as previous research has tended to identify women as more likely to experience anxiety and at greater levels.
In our article, ‘Anxious women or complacent men? Examining statistics anxiety in UK sociology undergraduates’, we wanted to revisit the core demographic variables of age and sex to examine their association with reported anxiety of statistics. Unlike most other research in the field however, we modelled an interaction between these two variables. This allowed us to explore whether reported anxiety of statistics varies within and between sexes by levels of age (comparing under 25s with those 25 and over).
The research is based on a secondary analysis of a dataset on the attitudes of sociology and political science students towards quantitative methods. These data, gathered by Williams et al. (2009) and shared on the UK data archive, are amongst the most comprehensive ever collected on attitudes of undergraduates to QM. Crucially, for our aims, the students were asked whether they felt anxious about learning statistics. This made it possible to interrogate these data to explore in detail the relationship between age, gender and anxiety of statistics.
The methods we used for the analysis are the same general techniques that many social science undergraduates will learn about during their own quantitative methods courses – logistic regression models and bivariate analysis. Our paper provides a simple applied account of these methods, which would be a relevant example in learning-teaching settings.
The results indicate that it is older men, not women, who are most likely to report experiencing anxiety of statistics in social science contexts. This is only apparent when considering the interaction between age and gender, without this interaction there is no difference between men and women in the likelihood of experiencing statistics anxiety.
It is therefore possible that young men, who are less anxious, have driven the gender differences that have previously been reported in research. This is to say that, rather than experiencing excessive anxiety, women may seem more anxious in previous studies because of their comparison to a group of more complacent young men.
The results call into question the potentially damaging ‘anxious women’ narrative that predominates the literature on the teaching-learning of maths and statistics. We suggest that this paradigm may be misleading, distracting, and an oversimplification. Despite the research focus on statistics anxiety, there is no strong evidence that it has a meaningfully negative influence on the learning of statistics for those on social science courses. By comparison, the pedagogical implications of an issue like complacency in this context has received little consideration. Overall, we argue that it is time to move away from the perception that women studying social sciences are excessively anxious of statistics. Our findings suggest that this is a myth in need of busting.
Photo by Priscilla Du Preez on Unsplash
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