Master’s Program

Please note that this Program was updated for students admitted beginning Fall 2011 and supersedes previous versions.

The regular Master's degree (Master of Arts in Statistics) is restricted to students who are already enrolled in a Ph.D. program at the University of Michigan in Ann Arbor. It is a dual degree earned while a student is working towards a Ph.D. in another field, aimed at students who do a significant amount of statistics as part of their thesis research. It is also awarded as an embedded degree to students working towards a Ph.D. in Statistics.

Students interested in a Master’s degree in Statistics who are not currently enrolled in a Ph.D. program at the University of Michigan, or whose Ph.D. thesis at Michigan does not involve a significant statistical component, should apply to the Master’s Program in Applied Statistics.

Application:

Applicants must have already been accepted by a Rackham Ph.D. program and should have a reasonable background in calculus, linear algebra, introductory probability, and introductory statistics.

Prospective applicants are encouraged to consult with the Department of Statistics prior to submitting an application. Students are strongly discouraged from completing the course requirements and then applying to the program. Note also that you must be enrolled in the program for one year and complete a writing component before the degree is awarded.

Applicants should submit a Dual Degree form to the Statistics Department Main Office (439 West Hall). A letter of recommendation from the applicant's Ph.D. Advisor is also required, along with an up-to-date CV and Statement of Purpose.

The Fall 2014 application deadline is April 1, 2014, and the Winter 2014 application deadline is December 1, 2013.

Curriculum:

The program requires a minimum of 24 credit hours of course work, including two cognate courses, and a writing component. Course selection must be pre-approved by the Program Advisor. Specifically, the requirements are:

STATS 500 (Applied Statistics 1) and STATS 503 (Applied Multivariate Analysis). More advanced students are encouraged to replace this sequence with STATS 600 (Linear Models) and STATS 601 (Analysis of Multivariate and Categorical Data) [6 credit hours]
BIOSTAT 601 (Probability) and BIOSTAT 602 (Theoretical Statistics). More advanced students are encouraged to replace this sequence with STATS 610 (Statistical Inference) and STATS 611 (Large Sample Theory). [at least 6 credit hours]
At least two elective statistics courses from graduate-level courses offered by the Department of Statistics or other approved courses (see list below). [at least 6 credit hours]
Two cognate courses from another department. Consult the Program Advisor about acceptable cognate courses. [at least 4 credit hours]
A writing component that demonstrates mastery of statistical methods in the design of data collection methods and/or modeling and analysis of data in the student's area of research. See more details below.

Students who have already taken courses that are equivalent to the required courses should discuss possible substitutions with the Program Advisor. Note that all students have to complete at least 24 credit hours in the program.

List of Elective Courses:

The following courses are acceptable as electives.

STATS 430: Applied Probability
OR
STATS 526: Discrete State Stochastic Processes (for more advanced students)

STATS 406: Introduction to Statistical Computing
OR
STATS 606: Statistical Computing (for more advanced students)
OR
BIOSTAT 615: Statistical Computing

STATS 504: Statistical Consulting

STATS 509: Statistics for Financial Data

STATS 531: Analysis of Time Series

STATS 535: Reliability
OR
BIOSTAT 675: Survival Time Analysis

STATS 547: Probabilistic Modeling in Bioinformatics

STATS 560: Introduction to Nonparametric Statistics

STATS 570: Design of Experiments

STATS 580: Methods and Theory of Sample Design

BIOSTAT 682: Applied Bayesian Inference

BIOSTAT 695: Analysis of Categorical Data
OR
SOC 619: Categorical Data Analysis.

BIOSTAT 696: Spatial Statistics

All STATS courses 600-level or above can be used as elective courses, with the exception that students can not use 600, 601 as electives if they have taken STATS 500, 503, and that they can not use 610, 611 as electives if they have taken BIOSTAT 601 and 602.

To obtain credits toward the degree requirement for cross-listed courses, students have to enroll under the STATS course number.

Writing Component:

Since the dual degree is primarily designed for students who do a significant amount of statistics for their thesis research, the students in the program are required to have a Ph.D. thesis chapter, or a thesis-based research paper submitted for publication, which demonstrates mastery of statistical methods at the level of a Master's project. The writing component may focus on data collection (design of experiments, survey design), modeling and analysis of data, or both. It must be approved by a member of the student's Ph.D. committee with an appointment in the Statistics department. This committee member will need to sign a form approving the statistical writing component, typically at the time of the defense. The student must also provide a two-page summary of the writing component, to be submitted with the signed approval form, describing the scientific problem under investigation, its importance, and statistical methods used.

In the event that the student's thesis does not have a sufficient statistical component, this requirement may be replaced with two additional elective courses (at least 6 credit hours), making the total credit requirement equivalent to that of the Master's Program in Applied Statistics. Students are strongly advised to consult with the Statistics faculty member on their committee well in advance of the defense to determine the best course of action. Those who do not anticipate having a significant statistical component in their thesis should apply directly to the Master's Program in Applied Statistics.

Master's Program in Statistics Checklist

Master's Program in Statistics before Fall 2011

Back to Degree Programs