Making an Impact: Creating a University Student-Driven Statistical Consulting Group for Non-Profits

A common problem in mathematics and statistics departments at academic institutions is providing students with experience working with real data in place of the often sanitized “toy” datasets used in the classroom. A solution can be creating mutually beneficial collaborations with local organizations and businesses. This paper discusses the creation of the Bryant University Statistical Consulting Office (BUSCO), and explores both its successes and challenges, with the purpose of guiding and inspiring other colleges and universities in establishing similar organizations. In particular, we discuss the challenges involved with obtaining funding, identifying and partnering with non-profits, and guiding students through meaningful and purposeful consulting experiences. We also share some note-worthy project outcomes.

AN OUTCOME-BASED STATISTICAL CAPACITY DEVELOPMENT PROGRAMME TO SUPPORT RESEARCH AT A UNIVERSITY

This paper addresses a critical component of the infrastructure necessary for professional development toward more effective teaching and learning of research and statistical methods. In particular, an interdisciplinary in-service model is proposed, which has the potential to better prepare educators to address institution-specific needs amidst dwindling resources. In particular, we present an outcome-based model for developing statistical capacity in research in response to the need for training statisticians in the academia. The aim of the programme was to equip selected faculty with the competencies needed to provide various forms of statistical support services in line with the research, extension, and publication mandate of a large private university in the Philippines. The programme was administered in three phases: (1) training phase, (2) statistical consulting and mentoring phase, and (3) “cascading or extension” phase. Evaluation of the outcome involves participants’ demonstration of learning in various statistical methods through serving as resource persons during the cascading activity and the documentation of the statistical consulting experiences made during the programme. First published February 2020 at Statistics Education Research Journal Archives

Updating Literacy Estimates in the Oklahoma City Metro

Project SCHOLAR (Statistical Consulting Help for Organizational Leaders and Academic Researchers) is an undergraduate student statistical consulting service at the University of Central Oklahoma. SCHOLAR students work under the supervision of faculty mentors from the Department of Mathematics and Statistics on various projects submitted from researchers on campus as well as off campus. This year, a SCHOLAR group was asked by the Oklahoma City Metro Literacy Coalition to update estimates of literacy levels in the Oklahoma City (OKC) Metropolitan Area and find factors related to below basic literacy proficiency. The group started by organizing and cleaning the data. Explanatory variables were collected from the 2010 US Census, and were used to develop a model for predicting the 2003 State Assessment of Adult Literacy estimates. The group performed a univariate analysis for each explanatory variable, using the p-value, residual plots, and QQ-plots to determine which variables were significantly related to literacy. The group performed multiple regression with stepwise selection, using all of the explanatory variables resulting from the univariate analysis after eliminating variables due to collinearity. The group intends to use the model along with the 2015 American Community Survey data to compute updated literacy estimates for every zip code in the OKC metro. The software used to perform this research is SAS and R.