Computable Statistical Research and Practice

The work of research and applied statisticians is driven by both manual and electronic computation. This computation, which supports our work, can be crudely described by 3 stages: scoping, to assess what can and needs to be done; analysis, where this is accomplished; and reporting, which communicates the results to others. Barriers to the reuse of computations can be found in the translational needs driving the transition between sub-activities; for example, scoping activities are seldom directly reusable during analysis, and there is a limited amount of direct reuse going from analysis to reporting. There is an additional high barrier for translating statistical theory and methodology to practical activities, with both sides (applied and theoretical statisticians) pointing the blame at the other for not using appropriate tools or addressing appropriate needs. In this sense, much statistical research is not really computable, but rather, translatable. This work describes some proposals for exploring novel information technology support to address the translational challenges during transition between stages of statistical practice. These are illustrated in the on-going design of CommonLisp Stat, a platform for investigating the interaction between statistical computing environments supporting research and/or practice.