Matt Stephenson, Read, Write, And Query Databases Using R

Speaker: Matt Stephenson, Data Management Specialist, Biofuels Economy Institute, ISU

Title: Read, Write, And Query Databases Using R

Abstract: Matt will show us the basics of establishing a remote connection to a password-secured database, querying its structure, downloading and uploading data to the database, and setting primary keys remotely.

Ulrike Genschel, A Modified t-test for Treatment Means in Unreplicated Classroom Comparisons

Speaker: Ulrike Genschel, Associate Professor, Department of Statistics, Iowa State University

Title: A Modified t-test for Treatment Means in Unreplicated Classroom Comparisons

Abstract: Discipline-based education research (DBER), with a focus on evidence-based teaching, has grown immensely over the last decades.  A common interest in DBER studies is identifying superior pedagogical approaches using rigorous and scientific methodology. Researchers may have few classrooms available when comparing classroom-level treatments or conditions so that one classroom per treatment is not uncommon in many DBER studies. 

Mitchell Krock, Tail Dependence as a Measure of Teleconnected Warm and Cold Extremes of North American Wintertime Temperatures

Speaker: Mitchell Krock, Postdoctoral Researcher, Argonne National Laboratory

Title: Tail Dependence as a Measure of Teleconnected Warm and Cold Extremes of North American Wintertime Temperatures

Matthias Katzfuss, Scalable Gaussian-Process Inference via Sparse Inverse Cholesky Factorization

Speaker: Matthias Katzfuss, Professor, Department of Statistics, University of Wisconsin-Madison

Title: Scalable Gaussian-Process Inference via Sparse Inverse Cholesky Factorization

Piotr Kokoszka, Detection And Localization Of Changes In Panels Of Random Densities

Speaker: Piotr Kokoszka, Professor, Department of Statistics, Iowa State University

Title: Detection And Localization Of Changes In Panels Of Random Densities

PhD Seminar: Zhili Qiao, "Some Clustering Methods for Omics Data"

Speaker: Zhili Qiao, PhD Candidate, Department of Statistics, Iowa State University

Title: Some Clustering Methods for Omics Data

Abstract: The advent of high-throughput sequencing technologies has significantly facilitated omics research over the past two decades, generating a vast volume of data. Unsupervised learning technologies such as cluster analysis serve as powerful tools to uncover hidden patterns and associations in omics data. However, the intricate natural structure and unique characteristics of omics data often make generic clustering methods inefficient or unsuitable.  

2024 Conference On Applied Statistics In Agriculture And Natural Resources