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Sharon L. Weinberg

Interim Department Chair; Professor of Applied Statistics and Psychology

Applied Statistics, Social Science, and Humanities


Sharon L. Weinberg is Professor of Applied Statistics and Psychology, a core member of PRIISM (Center for Practice and Research at the Intersection of Information, Society, and Methodology) and former Vice Provost for Faculty Affairs at New York University. She received an A.B. in mathematics and a Ph.D. in psychometrics and research design methodology from Cornell University. Dr. Weinberg has authored numerous articles, books, and reports on statistical methodology, statistical education, evaluation, and on such applied areas as clinical and school psychology, special education, and higher education. She is the recipient of several major grants, including a grant from the Sloan Foundation to support her current work with NYU colleague Ying Lu to analyze the correlates of test-taking behavior for the NYC Gifted and Talented programs. Her textbooks, Statistics Using IBM SPSS: An Integrative Approach, 3rd edition (2016) and Statistics Using Stata: An Integrative Approach, 1st edition (2016), both co-authored with former graduate student Sarah Knapp Abramowitz, are published by Cambridge University Press. Another of her books, Diversity in American Higher Education: Toward a More Comprehensive Approach, co-edited with NYU colleague Lisa Stulberg, and published by Routledge Press (2011), came out of her work as Vice Provost for Faculty Affairs at NYU.

She is a member, and former President and Chair, of the Board of the Jewish Foundation for Education of Women (JFEW), a foundation with an endowment of over $80 million that supports financially-needy women pursue their educational goals in undergraduate and graduate degree programs with scholarships, internships, and other program enhancements. She is a member of the President's Council of Cornell Women, where she has chaired its Development and University Relations Committees, and is a member of the Cornell University Council. Dr. Weinberg has served as President of the Special Interest Group of Educational Statisticians of the American Educational Research Association, a member of the Board of Directors of the Classification Society, and an elected member of the Society of Multivariate Experimental Psychologists. She is a member of the Editorial Advisory Board of the Educational Researcher, the journal of the American Educational Research Association. She is the recipient of Steinhardt’s Great Teachers Award and has twice received Steinhardt’s Daniel Griffith’s Award for Research.

Selected Publications

  • Sole, M.A. & Weinberg, S.L. (2017). What's Brewing? A statistics education discovery project. Journal of Statistics Education25(3), 137-144.
  • Lu, Y. & Weinberg, S.L. (2016). Public pre-K and test taking for the NYC gifted-and-talented programs: Forging a path to equity. Educational Researcher45(1), 36-47.
  • Klevan, S. & Weinberg, S.L., & Middleton, J. (2015). Why the boys are missing: A new explanation for the female advantage in college enrollment. Research in Higher Education, doi 10.1007/s11162-015-9384-9.
  • O’Connor, E., Scott, M.S., McCormick, M., & Weinberg, S.L. (2014). Early maternal attachment and behavior problems in middle childhood: The role of the subsequent caregiving environment. Attachment and Human Development16(6), 590 – 612.
  • Uyei, J., Coetzee, D., Macinko, J., Weinberg, S.L., Guttmacher, S. (2014). Measuring the degree of integrated tuberculosis and HIV service delivery in Cape Town, South Africa. Health Policy and Planning29(1), 42-55.
  • Uyei, J., Coetzee, D., Macinko, J., Weinberg, S.L., Guttmacher, S. (2014). The influence of integrated tuberculosis and HIV service delivery on patient outcomes. The International Journal of Tuberculosis and Lung Disease, 18(3), 315-321.


Applied Statistics for Social Science Research

Learn advanced quantitative research techniques and apply them to critical policy issues across social, behavioral, and health sciences.


Topics in Multivariate Analysis

This course is designed to meet the data analytic needs of the doctoral students whose dissertation relies on the analysis of quantitative data. Procedures important to the data analyst are covered including data entry and definition, treating missing data, detecting outliers, and transforming distributions. First term topics include multiple regression, analysis of covariance, repeated measures analysis of variance, and multivariate analysis of variance and covariance.Second term topics emphasize categorical data analysis, odds, rations, standardization, log linear models, logistic regression. Other topics include multinominal logistic models, survival analysis, principle components, and factor analysis. The approach is conceptual with heavy reliance on computer software packages. Appropriate for doctoral students desiring specialized knowledge beyond the introductory sequence
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Sharon L. Weinberg ,