Quantitative literacy (QL) – the ability to interpret, represent and communicate about numerical information in a “real world” context – is a desired learning outcome in most colleges and universities. However, because QL is not a discipline in itself, it is often unclear whose responsibility it is to teach it, what evidence demonstrates achievement, and what pedagogical practices lead to development of QL skills. The practice of biology is increasingly dependent on the ability to reason with numbers. The undergraduate biology curriculum, therefore, must incorporate opportunities for students to develop QL. Results/Conclusions On a case-based assessment at the beginning of the semester, we provided a table of raw data, and asked students to: (a) compute simple arithmetic means, (b) construct an appropriate graph, (c) articulate a claim based on the data, and, (d) provide justification (warrants) for their claim. Analysis of the assessment revealed that, at the beginning of the course, 57% of students correctly calculated and represented means on a graph; 10% correctly labeled the dependent variable (y axis); 29% formulated a complete and correct claim about the data; 27% provided appropriate reasoning to support their claim. Based on these data, we tailored instruction and assessment in the course to incorporate QL. Analysis of a problem embedded in the final exam provided evidence of students’ progress in their ability to graphically represent numerical data and to justify data-driven claims. Given a data set, 95% of students correctly calculated and plotted frequency values on a graph; 92% correctly labeled the y axis; 30% appropriately reasoned that a statistical test of significance would be necessary to support a claim based on the data.