Due to the ongoing COVID-19 Pandemic, the Statistics office staff are working remotely. If you need general assistance, please email us at stats@stat.colostate.edu. Thank you.

Welcome to the Department of Statistics at Colorado State University. Statistics is the science of inferring knowledge from data and describing uncertainty in those inferences. It plays a central role in scientific research, social policy, and governance. The Department of Statistics has a world-class record of success in education, research and service and has an out-sized impact on campus because of its engagement in educating students in all disciplines and interdisciplinary research.


Department Highlights

Recent Publication: "Eye trauma in falls presenting to the emergency department from 2006 through 2015"

Channing Parker served as a Statistical Consultant on a project at University of Pittsburgh in 2019, which resulted in a publication in early 2021. The paper, titled “Eye trauma in falls presenting to the emergency department from 2006 through 2015” by Bushra Usmani, Asad Latif, Mustafa Iftikhar, Yasir J Sepah, Channing Parker, Justin A Fliss, Kunal K Dansingani, and Syed Mahmood Ali Shah, was published in the British Journal of Ophthalmology on February 1st of 2021. The purpose of this project was to characterize the epidemiology of eye trauma in the event of falls presenting to the emergency departments (ED) in the USA.

Welcome to the Department: Channing Parker

Channing Parker recently joined the Department of Statistics as an instructor. They graduated from the University of Pittsburgh in 2019 with a Master’s degree in Statistics, after receiving their Bachelor’s in Mathematics and Statistics from James Madison University in 2017. Before joining the Statistics Department at CSU, they held a Visiting Instructor position at the University of Pittsburgh from 2019 to 2021. In their spare time, Channing enjoys various forms of art, including photography, macrame, and flower preservation, along with gardening, thrift shopping, and cuddling their dog, Finn. Welcome to the Department of Statistics, Channing!

Statistical faculty Wen Zhou is awarded NIHR01 grant to study the higher order dependence and protein functionality

Prof. Wen Zhou has been awarded a new NIH R01grant (1R01GM144961, 2021-2024) as the PI to study the higher order dependence in high dimensional data and its applications in learning protein functionality and structure. Collaborating with Prof. Zhao Ren from Statistics at University of Pittsburgh, Prof. Robert Jernigan from Biochemistry, Biophysics and Molecular Biology and Dr. Kejue Jia from Bioinformatics and Computational Biology at Iowa State University, in this project, Wen will tackle the important problem of quantifying and drawing inference on the higher order dependence, and biologically, how to integrate protein structure and sequence information in complex systems. Some of the most important characteristics of protein sequencing and structural data are the strong correlations buried within them, with the pairwise correlations in the sequence data already being routinely used to predict structural contacts. Here, the team will develop novel ways to use huge data sets to extract higher-order dependences, which are now possible with the availability of the large volumes of sequence data from genomics; and in addition, in the molecular structures such higher-order dependences are directly observable in the protein structures where groups of amino acids interact directly. Importantly, these higher-order dependences reflect the dense physical environment in the cell that requires for proper statistical characterization. A new model free information-theoretic measure is introduced to quantify the higher-order dependences, which serves as the central method in this project. By identifying the major challenges in drawing statistical inference based on this measure, the team will develop, evaluate, and improve a new statistical inference and computational framework for analyses of higher-order dependences with discrete data of a general type, motivated by the protein multiple sequence data. The new computationally efficient framework makes it possible to discover reliable higher-order dependences with the ability of quantifying uncertainty. The preliminary data here combine the information from sequences and structures to yield unexpected results that immediately relate to the dynamics of the protein structures. The outcome is an entirely new approach to handle the large volumes of protein sequence data and other omics data now available and the enormous volumes about to arrive on the doorsteps of omics analysts.

Jay Breidt named Chair of Census Scientific Advisory Committee

Jay Breidt has been selected to serve as Chair of the Census Scientific Advisory Committee (CSAC) for the US Census Bureau, beginning in August 2021. CSAC is organized under the Federal Advisory Committee Act and consists of experts from demographics, economics, geography, psychology, statistics, survey methodology, social and behavioral sciences, information technology and computing, marketing and other fields. The Committee advises the Director of the Bureau on the full range of Census Bureau programs and activities including communications, decennial census of population, demographic analysis, economic surveys and censuses, field operations, geographic analysis, information technology, and statistics.

New NSF grant to fund statistics research related to national security

Piotr Kokoszka (PI) and Haonan Wang and Indrakshi Ray received NSF grant “Threat Detection Based on Simultaneous Monitoring of Complex Signals from Multiple Sources” funded by the Division of Mathematical Sciences program “Algorithms for Threat Detection”. Motivated by threats to the operation of fleets of heavy vehicles, the research will develop statistical methodology and theory that will create foundations for a broad class of algorithms for real time detection of malicious attacks on various large scale operations. Statistical methodology will be based on probability in metric spaces and hidden Markov chains. Several PhD students will gain expertise at the intersection of advanced statistics, computer science and engineering.

Julia Sharp Continues Leadership in the American Statistical Association

Julia Sharp continues to be a leader in the American Statistical Association (ASA). Julia served on the ASA Board of Directors from 2017 until 2019. While on the Board of Directors, Julia led a Diversity and Inclusion Task Group. This Task Group initiated a diversity and inclusion resource repository and discussions with other entities to develop a diversity and inclusion consortium. Julia led the proposal for the Justice, Equity, Diversity, and Inclusion (JEDI) Outreach Group, which was approved by the ASA Board and is concluding its successful first year of existence. Julia is also serving as Chair of the ASA Council of Chapters Governing Board. Her initiatives have included modernizing chapter communication and obtaining historical chapter health information to help with leadership transitions and communication. Julia also serves on the Conference for Statistical Practice Steering Committee.


Upcoming Department Seminars,

Preliminary Exams,

& Ph.D. Defenses

Department Video Archive

Statistics Department Clubs & Organizations

Student Organized Activities and Research Seminars (SOARS)


Student Organized Activities and Research Seminars (SOARS) exists to encourage community and scholarship among graduate students in the statistics department and more broadly at Colorado State University.


See the SOARS website and full calendar of upcoming events here.

The Data Science and Statistical Learning Journal Club

The Data Science and Statistical Learning Journal Club

The Data Science and Statistical Learning Journal Club meets weekly to discuss papers and current work on topics relevant to data science and statistical learning. At the beginning of each semester, we will select a few interesting and latest manuscripts to study.

See the Data Science and Statistical Learning Journal Club website here.

Stat Alliance

CSU Stat Alliance

Stat Alliance is a student-led club welcome to all students with any level of interest or skill in statistics. Our meetings include hearing from guest speakers in the field of statistics,  making connections, social activities and much more!

See the Stat Alliance website and full calendar of upcoming events here.

Environmental Biostatistics Working Group

Environmental Biostatistics Working Group

The Environmental Biostatistics Working Group seeks to build collaboration and community among faculty and students working in biostatistics with application in environmental and public health.

See the Environmental Biostatistics Working Group website here.

Department News

Statistics master’s student wins Pediatric Traumatic Brain Injury Hackathon

Glenn Swanson, a recent graduate from the Applied Statistics Master’s Program, recently won first place in the Harmonized Pediatric Traumatic Brain Injury Hackathon, a competition to create statistical models that could potentially help in a health care setting.

Alex Hopkins builds on community she found on campus

Alex Hopkins found community through the Native American Cultural Center and Academic Advancement Center when she started at CSU. By the time she graduated, Hopkins was a peer mentor in both centers, as well as an accomplished alumna.

New Working Groups Generate Research Momentum

Even though the pandemic thwarted many activities in the Fall, three new working groups in the Department of Statistics generated research excitement in the areas of environmental biostatistics, data science and SAS programming.

Introducing STAT 100: statistical literacy

Although still in its infancy, data suggest STAT 100 has been successful at serving students for whom the quantitative reasoning requirement is a barrier to graduation, with completion rates ranging 92-100% .