## Statistics

### Field Description

The Field of Statistics offers two graduate degree programs: an MS/PhD degree in Statistics and a Masters of Professional Studies degree in Applied Statistics. The field does not offer a Masters degree in Statistics.

The PhD program is intended to prepare students for a career in research and teaching at the University level or in equivalent positions in industry or government. A PhD degree requires writing and defending a dissertation. Students graduate this program with a broad set of skills, from the ability to interact collaboratively with researchers in applied fields, through the formulation and computational implementation of novel statistical models and methods to demonstrating mathematically that these methods have desirable statistical properties. Cornell's PhD alumni have gone on to high profile positions in all of academia, industry and government.

The Master of Professional Studies (M.P.S.) degree in Applied Statistics is for persons interested in professional careers in business, industry or government. The M.P.S. program has three main components:

- A two-semester core course covering a wide range of statistical applications, computing, and consulting
- An in-depth statistical analysis project
- Elective coursework drawn from the resources of the Department of Statistical Science.

The program can be completed in one year by a well-prepared student with the equivalent of an undergraduate degree in statistics or applied mathematics. Students with less preparation can make up any missing prerequisites while at Cornell; in this case the program will take one to two years to complete.

M.P.S. or M.S./Ph.D.?

Statistics does not offer admission for those interested a terminal master's degree, but we do offer admission for those interested in pursuing a master's leading to a Ph.D. We also offer the M.P.S. in Applied Statistics, which is normally a one-year program that does not carry financial aid.

The M.P.S. is intended for persons who want a short-term (one year) master's degree so as to go into business, industry, or government statistical work. The M.P.S. is not equivalent to an M.S. on several counts: the M.P.S. has a project (a large-scale data-analysis project) rather than a thesis or a qualifying exam (which would be the case for an M.S.). The mathematical probability/statistics component of the M.P.S. is less than it would be for an M.S. (which would be considered the first part of a Ph.D.).

The admissions procedures are completely independent: at Cornell, if you want to go on for a Ph.D. after the M.P.S. you must to apply as a new student to the Ph.D. program; you would be considered as part of the "pool" of Ph.D. applicants and, if admitted, you might be able to apply some of your M.P.S. coursework, but there is no guarantee. The Ph.D. in Statistics at Cornell enrolls about 2 to 4 students each year; the M.P.S., about 20 to 25.

If you are applying for the M.P.S., please make clear your clear if you are applying for Option 1 or Option 2.

### Contact Information

Email: par246@cornell.edu

Phone: 607 255-8066

301 Malott Hall

Cornell University

Ithaca, NY 14853

### Subject and Degrees

**Applied Statistics (M.P.S. (A.S.))***(Ithaca)***Statistics (Ph.D.)***(Ithaca)*

### Concentrations by Subject

#### Applied Statistics

- applied statistics

#### Statistics

- biometry
- decision theory
- econometrics
- engineering statistics
- experimental design
- mathematical statistics
- probability
- sampling
- social statistics
- statistical computing
- stochastic processes

### Faculty

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*econometrics; sampling

**Research Interests:**data confidentiality; record linkage; econometric analysis of linked data; analysis of labor markets

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; mathematical statistics; statistical computing

**Research Interests:**high dimensional statistics time series, graphical models, genomics and financial econometrics

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*mathematical statistics

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*experimental design; mathematical statistics; statistical computing

**Research Interests:**computer intensive methods; generalized linear models; Monte Carlo simulation; statistical genomics

**Concentrations:**

*Statistics:*decision theory; mathematical statistics; probability

**Research Interests:**high dimensional modeling; sparsity; model selection; model averaging; non-parametric statistics; machine learning

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*probability; sampling

**Research Interests:**point processes; semi-Markov processes; species problems

**Concentrations:**

*Statistics:*mathematical statistics

**Research Interests:**machine learning, statistical inference, optimization and network inference,networked and transportation

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*probability

**Research Interests:**Stochastic processing networks Fluid and diusion models of queueing networks Impulse, singular and drift controls of diusions Customer contact center management Patient flow management in hospitals Semiconductor wafer manufacturing Revenue management Algorithm trading, orderbook dynamics

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*econometrics; mathematical statistics

**Research Interests:**likelihood inference; resampling methods; asymptotic approximations; linear models

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*statistical computing

**Research Interests:**Statistics, Machine Learning, Spatial Statistics, Exploratory Analysis, Semiparametric Regression, Predictive Analytics, Data Analysis, Observational data, Crowdsourced Data, and Citizen Science

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*probability

**Research Interests:**Optimal learning, sequential decision-making under uncertainty, and machine learning, focusing on applications in simulation optimization, design of experiments, materials science, e-commerce and medicine.

**Concentrations:**

*Statistics:*econometrics; mathematical statistics

**Research Interests:**nonparametric testing; econometrics

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; experimental design; mathematical statistics; sampling; statistical computing; stochastic processes

**Research Interests:**statistical learning theory; nonlinear functional data analysis; diagnostic and graphical statistics; nonlinear regression analysis

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*engineering statistics; mathematical statistics

**Research Interests:**Genomics statistics; shrinkage procedures including estimation, confidence intervals and multiple tests

**Concentrations:**

*Statistics:*engineering statistics; mathematical statistics; statistical computing

**Research Interests:**machine learning; text-mining; statistical learning theory; information access

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*decision theory; experimental design; mathematical statistics

**Research Interests:**optimization under uncertainty, casual inference, machine learning, personalization, online decision making

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; statistical computing

**Research Interests:**human population genetics; demographic inference

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*decision theory

**Research Interests:**econometrics; risk management; Bayesian statistics

**Concentrations:**

*Statistics:*statistical computing

**Research Interests:**poisson processes;marked point processes; gaussian processes; astrostatistics; astroinformatics; bayesian statistics; bayesian computation; bayesian experimental deisgn;functional data analysis; statistical software development

**Concentrations:**

*Statistics:*econometrics; social statistics

**Research Interests:**developing computational methods that leverage large scale genetic datasets to learn about human genetic history, evolution, and the genetic basis of human disease.

**Concentrations:**

*Statistics:*biometry; econometrics; engineering statistics; mathematical statistics; social statistics; statistical computing; stochastic processes

**Research Interests:**financial econmetrics; non parametric statistics; spatio-temporal statistics; biostatistics; machine learning

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; statistical computing

**Research Interests:**quantitative genetics/genomics; statistical genetics; computational biology; pathway modeling; molecular evolution

**Concentrations:**

*Statistics:*econometrics; mathematical statistics; sampling

**Research Interests:**econometrics; identification; survey methodology

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*mathematical statistics; statistical computing

**Research Interests:**high dimensional statistics semi parametrics, causal inference

**Concentrations:**

*Statistics:*mathematical statistics

**Research Interests:**mathematical statistics

**Concentrations:**

*Statistics:*engineering statistics; probability; stochastic processes

**Research Interests:**applied probability; extreme-value theory; data network analysis

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; engineering statistics; mathematical statistics; statistical computing

**Research Interests:**semiparametric regression; functional data analysis; splines and nonparametric estimation; astrostatistics; calibration and uncertainty analysis; environmental statistics

**Concentrations:**

*Statistics:*engineering statistics; probability; stochastic processes

**Research Interests:**probability theory

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*probability

**Research Interests:**Machine Learning, Statistical Learning Theory, Online Learning and Decision Making, Optimization, Empirial Process Theory, Concentration Inequalities, Game Theory

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; experimental design; sampling

**Research Interests:**Applied Statistics, experimental design, sampling

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*social statistics

**Research Interests:**Propensity scores Missing data Causal Inference Structural equation modeling

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; engineering statistics; experimental design; mathematical statistics; sampling; stochastic processes

**Research Interests:**biomedical statistics; reliability and life testing

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; experimental design

**Research Interests:**applied statistics

**Concentrations:**

*Statistics:*mathematical statistics

**Research Interests:**classification; copulas; empirical processes; high dimensional models; model selection; non parametric estimation; penalized empirical risk minimization

**Concentrations:**

*Statistics:*statistical computing

**Research Interests:**machine learning with a focus on metric learning, high dimensional data analysis, resource efficiency and learning scenarios that are used in web a biomedical applications

**Concentrations:**

*Applied Statistics:*applied statistics;

*Statistics:*biometry; decision theory; econometrics; mathematical statistics; sampling

**Research Interests:**Bayesian statistics; decision theory; empirical legal studies; epidemiology; social statistics; statistical bioinformatics; survival analysis

**Concentrations:**

*Statistics:*biometry

**Research Interests:**developing computational methods that leverage large scale genetic datasets to learn about human genetic history, evolution, and the genetic basis of human disease.

**Concentrations:**

*Statistics:*decision theory; engineering statistics; mathematical statistics; probability; sampling; statistical computing; stochastic processes

**Research Interests:**machine learning; artificial intelligence; data science; numerical analysis; probabilistic modeling; bayesian methods

**Concentrations:**

*Statistics:*decision theory; engineering statistics; probability; statistical computing

**Research Interests:**statistics

**Concentrations:**

*Applied Statistics:*applied statistics

**Research Interests:**proteomics and bioinformatics