Statistics

Graduate Degree Program Summary

Graduate programs offered

Earn a Graduate Degree

  • MS or PhD in Statistics
Areas of Study

These informal areas of focus may help to shape your course of study but they will not appear on transcripts.

  • Bioinformatics
  • Biometry
  • Environmental and Agricultural Statistics
  • Mathematical Statistics
  • Statistics in Sports
  • Survey and Behavioral Statistics

Online and Distance Opportunities

Some online coursework may be available for your program; contact dept. for details.

Contacts for Statistics


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Other Ways to Connect

On the Web
Statistics

Graduate Chair
Dr. Chris Bilder

Program Information
Stacey Herceg
sherceg2@unl.edu
402-472-1146

Campus Address
340 Hardin Hall North
Lincoln NE 68583-0963


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Application checklist and deadlines

1. Required by Graduate Studies

Submit these items as part of the standard steps to admission.

2. Required by Statistics

After you apply, allow one business day for us to set up your access to GAMES, where you'll complete these requirements.

  • Entrance exam(s): GRE
  • Minimum English proficiency:
    - Financial Consideration: Paper TOEFL 600, Internet TOEFL 100, IELTS 6.5
    - Otherwise: Paper TOEFL 550, Internet TOEFL 79, IELTS 6.5
  • Three recommendation letters
  • Statement of purpose

When sending GRE or TOEFL scores, UNL's institution code is 6877 and a department code is not needed.


Application Deadlines for Statistics
  • For Financial Consideration: January 15 for Fall. October 15 for Spring.
  • Otherwise: April 1 for Fall. October 31 for Spring.

Application/admission is for entry in a specific term and year. UNL's academic year is divided into 3 terms: Fall (August-December), Spring (January-May), and Summer (multiple sessions May-August). Some UNL programs accept new students only in certain terms and/or years; if your desired entry term isn't mentioned here, you may want to consult the department for clarification.

Description

Statistics as a discipline develops methods to collect and interpret data. Modern statistical methods are used in many areas, such as medicine, the biological and social sciences, economics, finance, manufacturing, marketing research, management, government, and research institutes.

Students who have majored in mathematics or statistics and have an interest in applications of these fields or students who have majored in other areas and have a good mathematics background should seriously consider a career in statistics. It is quite common for students to enter a statistics graduate program with only a few statistics courses since statistics is primarily a graduate discipline.

The Department of Statistics is involved in research, teaching, and statistical consulting for the entire university. Some of our faculty are involved in projects funded by federal agencies such as the National Science Foundation, Environmental Protection Agency, and United States Department of Agriculture. Because of its activities, the collaborative work with other disciplines gives graduate students a wide range of opportunities to work with individuals in these disciplines and to learn practical applications of statistical principles from direct experience. In addition, Ph.D. students have the opportunity to double major in statistics and economics.

Cost of attendance

Cost differs from one student to another. For details see Tuition, Fees, and Funding or try our Cost Estimator.

Courses and More

Admitted students will choose courses from the Course Catalog, typically in: During the first half of their coursework, students will work with an advisor to create a plan of study — one of the essential Steps to Degree Completion.

Faculty and research

Where available, faculty names link to bios or homepages and conversation icons () link to directory listings with address, phone, and email.

Chris Bilder

Categorical Data Analysis; Statistical Computing; Group Testing; Statistics in Sports

Erin Blankenship

Environmental Statistics; Nonlinear Models

Jennifer Clarke

Statistical Methodology with an Emphasis on High Dimensional and Predictive Methods; Statistical Computation; Bioinformatics/Computational Biology; Multi-Type Data Analysis; Bacterial Genomics/Metagenomics

Kent Eskridge

Decision Analysis; Design of Experiments; Biological Modeling

Kathy Hanford

Mixed Linear Models; Breeding and Genetics

Stephen Kachman

Mixed Linear Models; Plant and Animal Breeding and Genetics; Statistical Computing; Bioinformatics

Istvan (Steve) Ladunga

Computational Biology (Bioinformatics); Biostatistics; Epigenetics; Optimization; Machine Learning

David Marx

Spatial Variability; Design of Experiments; Linear Models; Statistics in Sports

Allan McCutcheon

Categorical Data Analysis; Survey Research Methods and Design; Cross-National and Comparative Survey Research

Julia Soulakova

Dose-Finding Strategies; Analysis of Single or Combination Drug Studies; Statistics in Behavioral Medicine

Walter Stroup

Generalized Linear Models; Design of Experiments; Statistics in Developing Countries

Shunpu Zhang

Bayes and Empirical Bayes Analysis; Estimating Animal Abundance

This summary page is maintained by Graduate Studies.
For additional details check out the dept./program website: Statistics.

Departments: Have an update for this summary? Contact Stacy Dam.