Consultants are well aware of the skills we must impart. These include: an appreciation for the role of the work one does in the context of the research effort; an understanding of what we can and cannot do as statisticians; a general appreciation for modeling and visualization; and an understanding of the nuclear elements of modeling tools. All of these skills contribute to one's ability to communicate ideas to a client and, ultimately, to the reader of any findings. Changes in the toolkit for statisticians require that we continually learn. In this talk I describe a process that creates a continual improvement cycle for the mastery of these skills. By mastery, I mean that the student has demonstrated understanding through the application of a principle and taught what they have done to others, including non-professionals. The principles, based on modeling and visualization efforts, give rise to the nuclear elements that are the simple and communicable features of the tool.
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