White and Gorard make important and relevant criticisms of some of the methods commonly used in social science research, but go further by criticising the logical basis for inferential statistical tests. This paper comments briefly on matters we broadly agree on with them and more fully on matters where we disagree. We agree that too little attention is paid to the assumptions underlying inferential statistical tests, to the design of studies, and that p-values are often misinterpreted. We show why we believe their argument concerning the logic of inferential statistical tests is flawed, and how White and Gorard misrepresent the protocols of inferential statistical tests, and make brief suggestions for rebalancing the statistics curriculum. [For the original article, "Against Inferential Statistics: How and Why Current Statistics Teaching Gets It Wrong," see EJ1152511. For the rejoinder, "Still against Inferential Statistics: Rejoinder to Nicholson and Ridgway," see EJ1152510.]