Integrating Computing into the Statistics Curricula
This project is a continued effort to explicitly address how we can
integrate various aspects of computing into the statistics curricula,
for both undergraduate and graduate programs. The aim is to
facilitate professors/instructors in different universisties and
colleges to both
 introduce new statistical/scientific computing
courses, and also
 increase the use of computing within existing
courses.
The primary aim is to teach computing as an additional
dimension of the statistics program, and not just to leverage it as a
medium by which to teach "traditional" statistical topics.
Nor are we focusing on using computing within the introductory
statistics class within this project.
While the project focuses on teaching computing content,
we also feel that this is a suitable vehicle for
 exposing students to modern statistical methods in a heuristic
fashion that illustrates that statistics is a dynamic and
changing field with relevance and many recent advances, and
 doing case studies and more involved data analyses from
beginning to end than students typically see in methodology classes
We believe this combination of topical problembased data analysis,
new methodology and rich computing and visualization is important for
statistical education and practice in this era of multidisciplinary,
datacentric scientific collaboration. We also feel that it will help
to attract talented students from different sources than we have
previously drawn from and to retain existing students who are
interested in ensuring that statistics and data analysis have an
impact on science and knowledge discovery.
Motivation
It is of
course obvious that all statistical analyses are done via a computer,
and that technology and computing advances dramatically influence
statistical practice. Yet very few programs teach students
more than elementary utilitarian computing skills.
Deliverables
The tangible outputs from this project include

 Sample syllabi for different courses. See also links to courses at Links to existing courses.


 Resources for teaching  lecture notes, exercises/homeworks/projects/casestudies,


 Workshops


 Papers to evangelize computing, technologies & data analysis within the community


 Talks (also to evangelize)


 Working with instructors in various institutions to introduce
and implement model classes,


 Text book on Data Technologies for Statistics.

Acknowledgements
This project is supported in part by the National Science Foundation grant DUE 0618865 and
DMS DMS 0636667.
Last modified: Sat Mar 7 14:03:50 PDT 2009