Statistics

Graduate Degree Program Summary

Graduate degrees offered

Degrees

  • M.S.; Ph.D.

Areas

Areas of Study
  • Bioinformatics
  • Biometry
  • Environmental and Agricultural Statistics
  • Mathematical Statistics
  • Statistics in Sports
  • Survey and Behavioral Statistics
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Contacts for Statistics

On the Web

Statistics

Graduate Chair

Dr. Kent Eskridge
keskridge1@unl.edu
402-472-7213

Campus Address

340 Hardin Hall North
Lincoln NE 68583-0963


Application checklist and deadlines

Required by the Office of Graduate Studies


See also: steps to admission.

Required by Statistics in GAMES

After you apply, allow one business day for us to establish your access to GAMES, where you'll complete these departmental requirements:

  • Entrance exam(s):
    - Domestic Applicants:  GRE recommended
    - International Applicants:  GRE
  • Minimum English proficiency:
    - Financial Consideration: Paper TOEFL 600, Internet TOEFL 100
    - Otherwise: Paper TOEFL 550, Internet TOEFL 79
  • Three recommendation letters
  • Department online form
  • Statement of purpose

Application Deadlines for Statistics
For Financial ConsiderationFall: January 15 Spring: October 15
OtherwiseFall: June 15 Spring: October 31

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.

Courses and More

Students in Statistics are most likely to take courses in: See also: Course Catalog in the Graduate Bulletin.

Students will work with an advisor to create a Program of Studies or Memorandum of Courses during the first half of their coursework.

Faculty and research

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, and 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
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
Anne Parkhurst
Chaos and Nonlinear Modeling; Multivariate Analysis; Time Series
James Schwenke
Julia Soulakova
Dose-Finding Strategies; Analysis of Single or Combination Drug Studies; Statistics in Behavioral Medicine; Drug Trials; Survey Design and Sampling
Walter Stroup
Generalized Linear Models; Design of Experiments; Statistics in Developing Countries
Dong Wang
Bioinformatics; Statistical Genetics; Non-Parametric Methods
Shunpu Zhang
Bayes and Empirical Bayes Analysis; Estimating Animal Abundance

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