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
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.
- introduce new statistical/scientific computing
courses, and also
- increase the use of computing within existing
While the project focuses on teaching computing content,
we also feel that this is a suitable vehicle for
We believe this combination of topical problem-based data analysis,
new methodology and rich computing and visualization is important for
statistical education and practice in this era of multi-disciplinary,
data-centric 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.
- 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
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.
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/case-studies,
- 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.
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