The primary goals of this Portfolio program are to:
  1. Offer a cohesive course of study for graduate students seeking to enhance the statistical modeling component of their research and to prepare for successful careers upon graduation.
  2. Provide a forum for graduate students from across UT to work together and exchange ideas regarding the application of statistical modeling methods to a broad range of areas.
  3. Leverage the existing expertise of faculty members in departments across UT whose research focuses on statistics at foundational and applied levels.

Students must complete 12 semester hours of courses as follows in "Course Requirements". Students are expected to obtain the consent of a Portfolio Adviser (selected from the list of faculty members affiliated with SDS) soon after entering the program to advise their course selections and guide their independent study.

How to Apply

Click HERE to download the application Applications are accepted on a rolling basis and should be sent to to GDC 7.408/D9800.

To be admitted into the program, a student must be in good standing in an approved graduate degree program. If applying before completing the first semester as a graduate student, the student must have a minimum cumulative undergraduate GPA of 3.0. If applying after completion of at least one full semester as a graduate student, the student must have a minimum cumulative graduate GPA of 3.0.

Course Requirements


A grade of an 'A' in SDS 380C Statistical Methods I

*Students who have taken one or more courses equivalent to the prerequisite course, and students who took SDS 380C but did not get an 'A', may take an exam administered by the Portfolio Committee. (Click HERE for more information).


SDS 380D Statistical Methods II


Choose two electives: Click here for a current list of approved electives. To ensure courses taken for the portfolio are interdisciplinary in nature, at least one of the two elective courses chosen must meet one of the following three criteria.

1. The elective is a SDS course (if cross-listed, it must be with a department other than the student's home department),
2. The elective is an approved elective course from outside the student’s home department,
3. The elective is in the student's department but outside the student's area (e.g., Counseling Psychology and Quantitative Methods are two separate areas, both within the Educational Psychology Department).


Under the supervision of a Portfolio Adviser, the student must successfully complete a research project (as part of a 3-credit independent study course) designed to apply advanced statistical modeling techniques to the student's research area of interest. The independent study should be conducted after all other coursework is complete or concurrently with the last program course. All students must present their final projects at the Portfolio Program's end-of-semester colloquium.  To register for the independent study course Download the Research Course form HERE. Click HERE for more details on the report.


Q: What are the requirements?

A: You will complete 12 semester hours, including a research project, as specified in the coursework guidelines. You must earn a letter grade of B or better in all courses required for certification and maintain an overall GPA of 3.5 or better in courses counting towards the Portfolio.

Q: How do I sign up?

A: Submit an application form to the SDS office in GDC 7.408, D9800. Students are encouraged to apply early in their course of graduate study. The SDS department will help each student choose an appropriate course sequence and find an adviser for his or her independent study project.

Q: Can Portfolio courses also fulfill my graduate degree requirements?

A: Depending upon the student's degree program, courses taken towards the portfolio may or may not count towards their degree.

Q: Will the portfolio appear on my transcript?

A: Yes. Your official UT transcript will state that you completed the Graduate Portfolio Program in Applied Statistical Modeling.

Prerequisite Exam

The 1.5 hour long exam will be held multiple times per year. Spring 2017 date:  April 13, 2017, 10:00 to 11:30 AM, GDC 7.402. To sign up for the exam, please contact Sasha Schellenberg at sasha.schellenberg[@]austin[dot]utexas[dot]edu by January 09, 2017.

The following topics will be covered: Descriptive Statistics (e.g., mean, median, standard deviation, skewness), Power, Type I and Type II Errors, p-values, z-scores, Bias, Consistency, Common Sampling Distributions, Interpreting Correlations, Confidence Intervals for Means, Hypothesis Testing for Means (using one sample, independent samples, and ANOVA), Chi-square Test of Independence, Simple Linear Regression, interaction.


Click to contact Vicki Keller at vicki.keller[@]cns[dot]utexas[dot]edu for more information.