In this paper I consider the characteristics of a statistically literate (a "statisticate") person. I suggest that a statisticate person should be able to read and understand statistical arguments of moderate complexity, and to carry out statistical analyses to some degree. Significantly, the truly statisticate person should also have developed the habit of thinking quantitatively. Furthermore, he or she does not rely on rigid rules to make statistical decisions, but uses informed judgment. In particular, he or she should understand the concepts of modelling and selection between models, and recognise their importance. Consideration is given to one of the major barriers to developing statistacy: the vocabulary used, in particular, the common use of two words that should only be used with the greatest of care (if used at all). These words are "prove" and "true". An important illustration of the way that vocabulary hinders the development of understanding is the case of hypothesis testing, a vital statistical tool that is widely misunderstood. It represents a mode of thought that is fundamental to statistical analysis, and so belongs in the kit bag of any statisticate person.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education