Nowadays we can not ignore the use of computers in statistics calculations and the main reason for its use is that computations become faster and trustworthy. Almost all statistical software computes p-values so students and researchers can take their decisions only based on its "usual" value. If the p-value is lower than 0.05 then the null hypothesis for a statistical test is "simply" rejected. Do statistical tests users ask about the meaning of this software output? If we are testing statistical hypothesis we have the null hypothesis tested against an alternative hypothesis. Do statistical tests users think about them? Since the decisions are based on sampling, the statistical tests decisions involve uncertainty and so two types of errors can be made. Do statistical tests users think about them? A questionnaire was constructed and administered to students and researchers in order to make a first approach about those subjects.
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