Adult SMA REACH: A UK clinical network and real-world data collection study for adults living with spinal muscular atrophy.

There is widespread agreement that statistics education needs to be improved (e.g., Carver et al., ; Moreira Da Silva & Pinto, ). Difficulties in learning and teaching statistics stem from a multitude of factors (Cousineau & Harding, ; Cui et al., ; Harth, ). On the learners' side, a major factor impeding the learning of statistics is students' fears, worries and apprehensions towards any form of statistical concepts or operations (Gibeau et al., ; Onwuegbuzie et al., ). This well‐documented phenomenon is known as (Esnard et al., ; Ruggeri et al., ; Williams, ; Zeidner, ). Statistics anxiety has three dimensions (Cantinotti et al., ; Gibeau et al., ; Vigil‐Colet et al., ). The first dimension concerns the anxiety towards exams and tests in a statistics course (). The second dimension is about asking the instructor or the teaching assistants for help in understanding something or doing an exercise (). Lastly, concerns the anxiety towards interpreting statistical results. This framework comes from the work of Vigil‐Colet et al. (), in which they developed the . It is the framework used herein as it has good factorial structure compared with the factor structure of a recent psychometric evaluation of the other leading framework in statistics anxiety; the (STARS; Nesbit & Bourne, ). Statistics anxiety is widely observed in university students (Chiou et al., ). In particular, Zeidner () reported a high level of statistics anxiety in 70% of Social Sciences students. Similarly, Onwuegbuzie and Wilson () reported that a majority of graduate students felt ‘uncomfortable’ with statistics. A more recent study reported that half of a large sample of college students enrolled in a wide range of programmes have moderate to severe statistics anxiety (Huang et al., ). According to previous research, statistics anxiety strongly influences grades in statistics courses. Specifically, Cantinotti et al. () reported a correlation of −.33 between these two variables (see also Fullerton & Umphrey, , and Chiesi & Primi, , for similar findings); making this variable one of the strongest predictors of the final grade and presumably, an important predictor of statistics . Identifying the determinants of statistics anxiety and better understanding how it relates to achievement in statistics could facilitate the development of learning activities to improve students' understanding of the underlying concepts of statistics. Indeed, as statistically literate citizens, people will be better qualified to contribute to societal discussions and debates in a world where policies need to be informed by relevant data (e.g., Cui et al., ; Lewin et al., ). A few reliable relations between statistics anxiety and other constructs are now well established, such as gender (Edirisooriya & Lipscomb, ; Mandap, , but see Gibeau et al., , which question this relation), achievement goals (Lalande et al., ; Valle et al., ), attitudes towards the subject (Chiesi & Primi, ; Macher et al., ; McIntee et al., ), and mathematics anxiety (Baloglu, ; Jordan et al., ; Zeidner, ). In the present studies, three cognitive factors that might be of statistics anxiety are examined. Those are working memory (WM), spatial anxiety, and mathematics anxiety.