StatisticsGraduate Program Summary |
Graduate Degrees OfferedM.S.; Ph.D. Specializations Bioinformatics Areas of Study Biometry; Environmental and Agricultural Statistics; Mathematical Statistics; Survey and Behavioral Statistics; Statistics in Sports Application ChecklistRequired by Office of Graduate Studies
Required by Statistics
Application Deadline For Financial Consideration Fall: March 1Otherwise Fall: June 15 Spring: October 31
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Statistical Principles
Statistics as a discipline develops methods to collect and interpret data. Modern statistical methods are used in several areas, such as medicine, the biological and social sciences, economics, finance, manufacturing, marketing research, management, government, and research institutes. |
Description of ProgramThe Department of Statistics is involved in research, teaching, and statistical consulting for the entire university. 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. 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. 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. |
ContactGraduate Chair Kent Eskridge402-472-7213 Department Address 340 Hardin Hall NorthLincoln NE 68583-0963 Department Website
http://statistics.unl.ed... |
Faculty and Research
| Chris Bilder | Categorical Data Analysis; Statistical Computing; Group Testing; Statistics in Sports | |
| Erin Blankenship | Environmental Statistics; Nonlinear Models | |
| 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 | |
| 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 | |
| Ananya Roy | Bayesian Methodology; Generalized Linear Models; Small Area Estimation; Robust Statistics; Biostatistics | |
| 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 | |
| Dong Wang | Bioinformatics; Statistical Genetics; Non-Parametric Methods | |
| Shunpu Zhang | Bayes and Empirical Bayes Analysis; Estimating Animal Abundance |


