The Center for Statistics and Machine Learning (CSML) specializes in data science education and research on campus. The center’s mission is to foster and support a community of scholars addressing the challenges of modern algorithmic data-driven research, the development of innovative methodologies for extracting information from data across different domains, and the education of students in the foundations of modern data science.
Data and Statistical Services (DSS) provides data and statistical consulting through experts who advise Princeton University student, faculty, and staff on choosing appropriate data, application of quantitative research methods, the interpretation of statistical analyses, data conversion, and data visualization.
Subject specialists help choose appropriate data. The statistical packages supported by consultants are R/R Studio, Stata, and SPSS. The DSS provides statistical and software assistance in quantitative analysis of electronic data as part of independent research projects, such as junior papers, senior theses, term papers, dissertations, and scholarly articles.
The PRDS provides Princeton University’s research community with expert services and infrastructure to store, manage, retain, and curate digital research data, and to make their digital research data available to the broader network of academic researchers, as well as the general public.
The Survey Research Center assists students, faculty, and administrators with the design and implementation, and management of their survey research projects. The SRC provides consultation and guidance on study design, sampling, instrument development, data collection and data processing. The Center has digital voice recorders, iPads, a 12-station computer-assisted telephone interviewing (CATI) facility, a library collection on survey research methods, and a network of external resources.
The DDSSI is participating in the Social Science One initiative being led by the IQSS. This initiative is an effort to build partnerships between academic researchers and private companies that house massive amounts of data. The goal of the project is to streamline the process of navigating the myriad regulatory, institutional, university, privacy, and other hurdles involved in negotiating access to and approval for the use of corporate data.