Student Learning Outcomes: PhD in Statistics

1. The ability to carry out research in statistical science.

2. The ability to access and read statistical literature.

3. An understanding of the major modes of statistical inference: frequentist, decision theoretic, Bayesian, and likelihood.

4. Knowledge of statistical procedures based on computation and simulation.

5. The ability to communicate with applied scientists and the statistical community.

Summary of Progress on PhD Assessment

Student learning outcomes (SLOs) and an alignment matrix have been developed and posted on the Statistic’s Department Website. The alignment matrix lists courses, qualifying exams, and a dissertation as tangible criteria that will be used to assess how the PhD program aligns with SLOs. Preliminary exams, a research update, and a final defense are also listed, as is an exit interview. To supplement evaluation of the PhD program, survey forms for the preliminary exam and final exam have been drafted for the collection of quantitative data from faculty and students for program assessment. The survey form for the preliminary exam has been “piloted” for several cases and some initial data collected. Based on feedback from faculty that have completed this survey, some minor revisions may be made to improve the tracking of assessment criteria in the surveys to departmental and university SLOs.