Research in Statistics
Faculty and students in the Department of Statistics at Penn State are developing statistical and computational techniques to address some of the most challenging and exciting scientific questions facing the world today. Their theoretical and methodological work advances the forefront of the disciplines of statistics and data science, while the interdisciplinary nature of their research addresses some of the most important and exciting topics of our time such as genetics, data privacy, infectious diseases, public health, astronomy, climate and environmental science.
Astrostatistics
The center for Astrostatistics serves as a crossroads where researchers at the interfaces of statistics, data analysis, astronomy, space and observational physics collaborate and share methodologies, and together prepare the next generation of researchers.
Bayesian Statistics
Bayesian methods have become extremely valuable in scientific research over the past three decades as new computer algorithms and vast technological improvements in computing have allowed hierarchical Bayesian models to be fit to complex data.
Biostatistics/Bioinformatics
Statistical methods have always been instrumental to the life sciences and biomedical research, and they have become even more critical with the advent of contemporary high-throughput techniques in genomics, epigenomics, and electronic medical records.
Business Analytics
Business analytics research explores the best techniques to model, analyze and use the large quantity of readily available data effectively. Research areas include data mining, forecasting, information system strategy, and optimization.
Computational Statistics
It is virtually impossible to separate modern statistics from computing. This has led to computational statistics – the study of algorithms designed to solve computational problems that arise in statistics – being a discipline of its own within statistics.
Functional Data Analysis
Functional Data Analysis is a branch of statistics that emerged out of nonparametric statistics to study data where one or more variables can be viewed as a curve, surface, or other type of function. Research includes clustering and dimension reduction.
High-Dimensional Data
Information and technology have revolutionized data collection. High-dimensional data, including, but not limited to, genetic data, image data such as Magnetic resonance imaging (MRI), surveillance video data and network data, are valuable in statistical analysis.
Imaging Science
Forty-thousand years ago, our ancestors documented their history on stone. Today, discovery and innovation depend on the production of digital images while social media allows the sharing of billions of digital photos per day online.
Social Science
Many of the most exciting recent developments in social science research have been driven by the availability of new data sets where the size and complexity of the data require the development of new statistical methods.
Spatiotemporal Data
Penn State Statistics has several faculty who work on developing new spatial and spatiotemporal models to address scientific questions from a wide variety of disciplines, for instance studying the spread of infectious diseases and the ecology of lakes.
Statistical Network Science
In the interconnected world of the twenty-first century, networks are ubiquitous. Penn State Statistics has one of the world’s leading research groups in statistical network science, with research topics including latent structure models and computational methods.
Machine Learning
Statistics Education
Research in this area studies methods for teaching, learning, and assessment in statistics education including comprehensive preparation for aspiring professionals to prepare the broader populace to critique information as we make decisions and shape our views.
Collaborations
Our faculty work closely with graduate students, undergraduates, postdoctoral fellows, and other faculty. These collaborations serve both to accomplish research that would otherwise not be possible and to mentor new researchers on the research process. For our Ph.D. students and undergraduates, research on statistical methodology and applications often leads to doctoral dissertations and undergraduate theses.
Many of the greatest statistical innovations have come when statisticians have worked on solving hard scientific problems from other disciplines. A famous early example of this is Fisher's seminal contributions to likelihood theory and the design of experiments while working on problems in genetics and agriculture. At the Penn State statistics department—where Fisher's student and legendary statistician in his own right C.R. Rao was a faculty member—we have a tradition of interdisciplinary research. Many of our faculty work closely with researchers in a wide variety of disciplines like biology, atmospheric science, neuroscience, astronomy, and public health.
These research collaborations involve our graduate and undergraduate students and are great ways for students to learn about how statistical methods can solve real-world problems. Working across disciplines also really strengthens communication skills that contribute to our students' success whether they choose to go into academics or industry or government.
Seminars
Statistics Department Colloquia
The Statistics Department Colloquia invites academic scholars and industrial researchers to present and communicate cutting-edge research and progress in statistics, machine learning, data science, and their interdisciplinary applications. Colloquia are held weekly and open for attendance by faculty, students, and staff.
Stochastic Modeling and Computational Statistics (SMAC) Talks
The SMAC seminar series features speakers from within Penn State. The talks are given by graduate students, postdocs, and faculty from both Statistics as well as other departments where statistical questions feature prominently in the research. This forum gives people an opportunity to hear about the exciting research being conducted right here at Penn State, and often leads to new collaborations. It is very informal and interactive, and often features ongoing work, which makes it particularly popular with students and faculty. SMAC Talks are held weekly during the academic year.
Graduate Students
We offer two distinct programs of study for our graduate students—leading to a doctorate in statistics and a master of applied statistics (M.A.S.). We also offer two additional dual degrees that can be obtained in conjunction with a degree in statistics. Students may also pursue concurrent M.S. degrees in statistics or a related field, while students from other disciplines may consider obtaining a graduate minor in statistics. Learn more about our programs.
Centers and Institutes
The department has connections to a number of research centers across the university. Many members of the department are also associated with centers in the Huck Institutes. The Center for Astrostatistics is housed within the department and is lead by Professor Jogesh Babu.
Departmental Centers
The Center serves as a crossroads where researchers at the interfaces between statistics, data analysis, astronomy, space and observational physics collaborate, develop and share methodologies, and together prepare the next generation of researchers.
CLIMA brings together scholars to catalyze transformative, integrated research on climate change, mitigation, adaptation, and decision making that transcends disciplinary boundaries and advances real-world climate risk management.
We provide statistical advice and support to Penn State researchers and external clients in industry and government.
The SCC provides support in the following areas:
- Research Planning
- Design of Experiments and Survey Sampling
- Statistical Modeling and Analysis
- Analysis Results Interpretation
- Advice on appropriate software for data analysis
The research interests of SLDM@PSU include:
- Statistical Learning and Data Mining
- High Dimensional Hypothesis Testing
- Statistical Analysis of Big Data and Large Networks
- Statistical Modeling in Health Science, Information Science, and Business Analytics
Centers and Institutes within the Huck Institutes of the Life Sciences
The Huck isn't easy to explain. It covers a lot of ground. It might best be imagined as a web—or maybe as a series of bridges, built and maintained by dedicated laborers, between various University institutions that would have otherwise been isolated islands.
The more these bridges are built up, the better we get at communicating and collaborating across the life sciences, and the better we get at solving problems.
Bringing together researchers in medicine, genomics, molecular biology and statistics to advance basic genomic research and translate that research into new diagnostic, therapeutic, and preventive medical strategies.
The Center for Statistical Genetics, housed within the Department of Public Health Sciences and the Department of Statistics, offers an interdisciplinary forum that convenes geneticists who are designing and running the experiments, statisticians who are analyzing and interpreting the data, and software engineers who are developing the computing tools into a cohesive, comprehensive team.
Comprising the Center for Infectious Disease Dynamics and the Center for Molecular Immunology and Infectious Disease, the Infectious Disease Institute and its faculty are at the leading edge of infectious disease research at Penn State.
The Institute and its faculty also support the Huck Institutes' Immunology and Infectious Diseases emphasis area in the MCIBS graduate program.
https://www.huck.psu.edu/institutes-and-centers/infectious-disease-institute
CIDD embraces all scales and components of infectious disease biology. Our interdisciplinary approach, coupled with a dynamic viewpoint, provides insight into how to prevent or reduce infections.
https://www.huck.psu.edu/institutes-and-centers/center-for-infectious-disease-dynamics
Other University Centers
ICDS helps you apply big data and big simulation methods across the research landscape.
The Methodology Center is an interdisciplinary research center within the College of Health and Human Development at the University Park campus of Penn State. We develop and disseminate new methods for social, behavioral, and health sciences research focusing on vital public health issues, including substance abuse and HIV.
The mission of The Methodology Center is to advance public health by improving experimental design and data analysis in the social, behavioral, and health sciences.
QuantDev is a core of methodologists at Pennsylvania State University – primarily with backgrounds in quantitative psychology and statistics. We aim to stimulate, coordinate, support, and disseminate research and teaching about the use of quantitative methods in social science.
Penn State Clinical and Translational Science Institute (CTSI) provides tools, services and training to make health research more efficient at Penn State. It is an advocate for translational science and is a bridge between basic scientists and clinical researchers. The institute promotes collaboration to discover new treatments, medical procedures and ways to diagnose disease.
Communities
Penn State Data Science encompasses the multidisciplinary and still-evolving field of data science. This site provides a hub where current and prospective students, faculty, and industry partners can learn about academic programs, areas of research, and events of interest to the broader data science community.
Research News
Three teams from the Penn State Eberly College of Science have received ICDS seed grants.
New risk scores developed by Penn State biologists could help clinicians identify young children most at risk of developing obesity.
