Formal inference, which makes theoretical assumptions about distributions and applies hypothesis testing procedures with null and alternative hypotheses, is notoriously difficult for tertiary students to master. The debate about whether this content should appear in Years 11 and 12 of the "Australian Curriculum: Mathematics" has gone on for several years. The statistics education research community has been discussing the lead in to inference, through informal inference, for some time, and for example the fifth Statistical Reasoning, Thinking and Literacy Forum (SRTL-5 in 2005) had informal inferential reasoning as its theme. Over the last few years various phrases have been used to describe the concept. Ben-Zvi (2006) used IIR (informal inferential reasoning), whereas Pratt and Ainley used ISI (informal statistical inference). Makar and Rubin (2009) presented a useful framework that can be summarised as context and a question, where "evidence" is used to make a "generalisation" beyond the data with an acknowledgement of "uncertainty." Moving to the stage of informal inference where randomness is deliberately introduced into the study design through random sampling and/or random assignment, "resampling" methods offer a way of evaluating evidence to support a generalisation that can be reported with an associated frequency-based probability. In this article, the authors discuss how to build intuitions about statistical inference based on resampling. They present some steps that illustrate the resampling (without replacement) procedure for comparing groups without having to write instructions in a software language. (Contains 10 figures, 2 footnotes and 1 table.)