Many students are introduced to computing through its infusion into other school subjects. Advocates argue this approach can deepen learning and broaden who is exposed to computing. In many cases, such interdisciplinary activities are student-driven and collaborative. This requires students to balance multiple learning goals and leverage knowledge across subjects. When working in groups, students must also negotiate this balance with peers based on their collective expertise. Balance and negotiation, however, are not always easy. This paper presents data from a project to infuse computing into high school statistics using the R programming language. We analyze multiple episodes of video data from two pairs of students as they negotiated (1) the statistics and computing goals of an activity, (2) the knowledge needed to meet those goals, and (3) whose expertise can help achieve those goals. One pair consistently reached agreement along these dimensions, and engaged productively with both subject matter and computing. The other pair did not reach agreement, and struggled to accomplish their tasks. This work provides examples of productive and unproductive interdisciplinary computing collaborations, and contributes tools to study them.