Twin Cities campus
 
Twin Cities Campus

Statistics Ph.D.

Statistics, School of
College of Liberal Arts
Link to a list of faculty for this program.
Contact Information
Department of School of Statistics, 313 Ford Hall, 224 Church Street SE, Minneapolis, MN 55455 (612-625-8046; fax: 612-624-8868)
  • Program Type: Doctorate
  • Requirements for this program are current for Spring 2018
  • Length of program in credits: 70
  • This program does not require summer semesters for timely completion.
  • Degree: Doctor of Philosophy
Along with the program-specific requirements listed below, please read the General Information section of this website for requirements that apply to all major fields.
The School of Statistics is the primary venue at the University for research, teaching, and dissemination of the theory, methodology, and applications of statistical procedures. Students may specialize in any area of statistics. The core program for all students has strong components of both theoretical and applied statistics.
Program Delivery
  • via classroom (the majority of instruction is face-to-face)
Prerequisites for Admission
International applicants must submit score(s) from one of the following tests:
  • TOEFL
    • Internet Based - Total Score: 79
    • Internet Based - Writing Score: 21
    • Internet Based - Reading Score: 19
    • Paper Based - Total Score: 550
  • IELTS
    • Total Score: 6.5
  • MELAB
    • Final score: 80
Key to test abbreviations (TOEFL, IELTS, MELAB).
For an online application or for more information about graduate education admissions, see the General Information section of this website.
Program Requirements
34 credits are required in the major.
12 credits are required outside the major.
24 thesis credits are required.
This program may be completed with a minor.
Use of 4xxx courses toward program requirements is permitted under certain conditions with adviser approval.
A minimum GPA of 3.00 is required for students to remain in good standing.
At least 2 semesters must be completed before filing a Degree Program Form.
Required Courses
Core Courses
STAT 8051 - Advanced Regression Techniques: linear, nonlinear and nonparametric methods (3.0 cr)
STAT 8052 - Applied Statistical Methods 2: Design of Experiments and Mixed -Effects Modeling (3.0 cr)
STAT 8053 - Applied Statistical Methods 3: Multivariate Analysis and Advanced Regression (3.0 cr)
STAT 8054 - Statistical Methods 4: Advanced Statistical Computing (3.0 cr)
STAT 8111 - Mathematical Statistics I (3.0 cr)
STAT 8112 - Mathematical Statistics II (3.0 cr)
STAT 8801 - Statistical Consulting (3.0 cr)
STAT 8913 - Literature Seminar (1.0 cr)
Statistics Electives
Courses from other departments with heavy statistical content, and some 5xxx-level statistics courses may be used as electives. Students choose courses in consultation with the director of graduate studies.
Take 12 or more credit(s) from the following:
· STAT 8xxx
Outside Coursework
Take MATH 8651 (3 cr) and MATH 8652 (3 cr). Coursework comparable to MATH 8651 and 8652 may be substituted with approval of the director of Graduate Studies.
MATH 8651 - Theory of Probability Including Measure Theory (3.0 cr)
MATH 8652 - Theory of Probability Including Measure Theory (3.0 cr)
Electives
Take at least 6 additional credits to complete the 12-credit outside coursework requirement.
Thesis Credits
Take 24 or more credit(s) from the following:
· STAT 8888 - Thesis Credit: Doctoral (1.0-24.0 cr)
 
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STAT 8051 - Advanced Regression Techniques: linear, nonlinear and nonparametric methods
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Linear/generalized linear models, modern regression methods including nonparametric regression, generalized additive models, splines/basis function methods, regularization, bootstrap/other resampling-based inference. prereq: Statistics grad or instr consent
STAT 8052 - Applied Statistical Methods 2: Design of Experiments and Mixed -Effects Modeling
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Design experiments/analyze data with fixed effects, random/mixed effects models. ANOVA for factorial designs. Contrasts, multiple comparisons, power/sample size, confounding, fractional factorials. Computer-generated designs. Response surfaces. Multi-level models. Generalized estimating equations (GEE) for longitudinal data with non-normal errors. prereq: 8051 or instr consent
STAT 8053 - Applied Statistical Methods 3: Multivariate Analysis and Advanced Regression
Credits: 3.0 [max 3.0]
Prerequisites: PhD student in stat or DGS permission and 8052
Grading Basis: A-F or Aud
Typically offered: Every Fall
Standard multivariate analysis. Multivariate linear model, classification, clustering, principal components, factor analysis, canonical correlation. Topics in advanced regression. prereq: PhD student in stat or DGS permission and 8052
STAT 8054 - Statistical Methods 4: Advanced Statistical Computing
Credits: 3.0 [max 3.0]
Prerequisites: STAT 8053 or #
Grading Basis: A-F or Aud
Typically offered: Every Spring
Optimization, numerical integration, Markov chain Monte Carlo, related topics. prereq: STAT 8053 or instr consent
STAT 8111 - Mathematical Statistics I
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Probability theory, basic inequalities, characteristic functions, and exchangeability. Multivariate normal distribution. Exponential family. Decision theory, admissibility, and Bayes rules. prereq: [5102 or 8102 or instr consent], [[Math 5615, Math 5616] or real analysis], matrix algebra
STAT 8112 - Mathematical Statistics II
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Statistical inference, estimation, and hypothesis testing. Convergence and relationship between convergence modes. Asymptotics of maximum likelihood estimators, distribution functions, quantiles. Delta method. prereq: 8111
STAT 8801 - Statistical Consulting
Credits: 3.0 [max 3.0]
Prerequisites: STAT 8051 and STAT Grad Student or Instructor Consent
Grading Basis: S-N or Aud
Typically offered: Every Spring
Principles of effective consulting/problem-solving, meeting skills, reporting. Aspects of professional practice/behavior, ethics, continuing education. prereq: STAT 8051 and STAT Grad Student or Instructor Consent
STAT 8913 - Literature Seminar
Credits: 1.0 [max 4.0]
Grading Basis: S-N only
Typically offered: Every Fall & Spring
Students will read, present, discuss, and critique current literature/research. prereq: Statistics grad major or instr consent
MATH 8651 - Theory of Probability Including Measure Theory
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Probability spaces. Distributions/expectations of random variables. Basic theorems of Lebesque theory. Stochastic independence, sums of independent random variables, random walks, filtrations. Probability, moment generating functions, characteristic functions. Laws of large numbers. prereq: 5616 or instr consent
MATH 8652 - Theory of Probability Including Measure Theory
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Conditional distributions and expectations, convergence of sequences of distributions on real line and on Polish spaces, central limit theorem and related limit theorems, Brownian motion, martingales and introduction to other stochastic sequences. prereq: 8651 or instr consent
STAT 8888 - Thesis Credit: Doctoral
Credits: 1.0 -24.0 [max 100.0]
Grading Basis: No Grade
Typically offered: Every Fall & Spring
(No description) prereq: Max 18 cr per semester or summer; 24 cr required