Department of Statistics and Biostatistics
Graduate Programs
Assessment of Student Learning Outcomes
Our programs include an MS program and a PhD program.
MS Program
Program Description
Our MS program requires 30 credits in
approved graduate courses; these credits are almost invariably earned
through 10 three-credit courses. Coursework involves core courses in
probability, statistical theory, experimental design, regression, and
the interpretation of data. MS candidates are also required to pass
a two-part comprehensive exam on statistical theory and practice,
and to complete an MS essay.
Program Goals
Our MS graduates are expected to function as independent applied
statisticians. These graduates should be prepared for careers in
industry, government, the non-profit private sector, and in non-faculty
academic positions. As such, they are expected to draw on traditional and
newly-emerged statistical techniques, identify the appropriateness of a
particular technique to a particular data context, apply the technique,
either using hand calculation, or more commonly, using tested and
verified standard statistical software, to appropriately interpret the
results of such calculations, to report the results to practitioners
knowledgeable in the field that generated the data, and to make minor
extensions to these techniques.
Student Assessment
Candidates for admission to the MS
program submit transcripts, letters of recommendation, and GRE scores.
Transcripts are examined for evidence of mathematical competence through
a second course in calculus and a course in linear algebra, and for
evidence of statistical experience through a senior-level undergraduate
methods course. Deficiencies in background are noted, and remediation
of deficiencies is made a condition for admission.
A systematic set
of prerequisites is enforced by the registrar, stopping students from
registering for courses that they do not have the academic background for.
Students are allowed to count toward their degree no more than two
courses with grades below B. Grades below B, and incomplete grades,
are tracked by the secretary to the graduate director and called to the
graduate director's attention. Students with more than one sub-B grade,
or with more than one pending incomplete, are instructed to discuss the
situation with the graduate director. Our MS program is designed to
be completed part-time, and students completing less than 9 credits per
year are also instructed to meet with the graduate director. Systematic
tracking of degree candidates is performed via the GradPortal system.
Aside from course assessment, students are also assessed through the
comprehensive exam, consisting of a theoretical and an applied section.
Questions are set with the goal of assessing core competence in
statistical application and theory, and the grading rubric is devised
to calibrate passing with a confidence in the ability to function
independently. Students are also required to complete an MS essay,
demonstrating the ability to competently report the results of a complex
statistical analysis.
Program Assessment
The faculty of Statistics and Biostatistics continuously reevaluates
our graduate courses, to obtain courses with the following properties:
-
Core applied courses should contain the knowledge base currently required
of all practicing applied statisticians.
-
Core theoretical courses should be the gateway for self study for mastery
of techniques that become part of the standard statistical toolbox as
the field of statistics develops.
-
Optional courses (including doctoral level courses accessible to
our strongest MS students) should allow an introduction to emerging
statistical techniques.
Exams are continuously assessed by examining the relationship between
course grades and exam success, and the relationship between course and
exam content.
PhD Program
Program Description
Our PhD program requires 48 credits in
approved graduate courses; these credits are almost invariably earned
through 16 three-credit courses. Coursework involves core courses in
probability, statistical theory, and statistical methodology.
PhD candidates are also required to pass
a written exam on statistical theory,
and an oral exam on advanced theory and statistical practice.
Our PhD candidates must also write and defend a thesis consisting of
original research.
Program Goals
We prepare our PhD graduates for careers as scholars.
Central to their career is the pursuit of an ongoing research agenda.
This research agenda is important, both for its own sake, and for its
support of teaching and statistical practice.
Students also receive direct preparation for teaching and statistical practice.
PhD graduates engaged in statistical practice are prepared for analyses of
data of nonstandard sources and structures, and are expected to
develop and implement new statistical techniques. These graduates can also
be expected to take leadership roles in their organizations.
Student Assessment
Candidates for admission to the PhD
program submit transcripts, letters of recommendation, and GRE scores.
Transcripts are examined for evidence of mathematical competence through
real analysis, and for
evidence of statistical experience through a senior-level undergraduate
methods course. Deficiencies in background are noted, and remediation
of deficiencies is made a condition for admission.
A systematic set
of prerequisites is enforced by the registrar, stopping students from
registering for courses that they do not have the academic background for.
Grades below B, and incomplete grades,
are tracked by the secretary to the graduate director and called to the
graduate director's attention. Students with more than one sub-B grade,
or with more than one pending incomplete, are instructed to discuss the
situation with the graduate director.
Systematic tracking of degree candidates is performed via the GradPortal system.
Aside from course assessment, students are also assessed through the
written and oral exams.
Questions are set with the goal of assessing core competence in
statistical theory, and the grading rubric is devised
to calibrate passing with a confidence in the ability to successfully
complete a thesis.
Students are also required to complete a dissertation
demonstrating the ability to perform original research.
Program Assessment
The faculty of Statistics and Biostatistics continuously reevaluates
our graduate courses, to obtain courses with the following properties:
- Core theoretical courses should give PhD students an understanding
of traditional statistical principles, an understanding of the range of
problems conventionally included in the discipline of statistics,
an understanding of the various conventional solutions to these problems, and
the vocabulary necessary to communicate the ideas involved in these problems
and solutions. This body of knowledge is meant as a point of departure for
the student's own thesis work, and not as a constraint on the scope of this
work.
- Optional courses should allow an introduction to emerging
statistical areas.
- Courses in applied methodology, often taken with MS students, should
provide a background in contemporary statistical practice, with the aims of
preparation for that portion of a career devoted to applications, and of
exposure to possible research areas.
- Courses in statistical computing should prepare students for the implementation of emerging statistical techniques.
Exams are continuously assessed by examining the relationship between
course grades and exam success, and the relationship between course and
exam content.
