The UB Summer Research Institute trains researchers in a collegial, intellectually engaging and multidisciplinary atmosphere. Workshop participants learn easy to understand practical information about statistics and methods, developing skills and knowledge to confidently analyze their own data. Our courses are appropriate for a range of researchers, including graduate students from all disciplines, private and public sector researchers and policymakers, and college and university faculty. Anyone with research experience/training who is interested in gaining new skills, or brushing up on the latest analytic techniques, is welcome.
Prof. Erin Hatton
Take a deep dive into familiarizing yourself with qualitative data analysis, focusing on in-depth interviews and content analysis. Learn how to develop thematic codes, apply them to qualitative data, and analytically interpret the results. You will conclude with an in-depth review about writing and presenting the results of such analyses.
Session 2: Focus Group Research, May 20–21
Prof. Veronica Horowitz
Learn the fundamentals of conducting focus group research and the variety of purposes that focus group research serves. Specific topics will include planning a focus group (developing questions, selecting participants, and selecting an appropriate setting); moderating and notetaking skills; analyzing focus group data; and organizing and reporting results.
Session 3: Social Network Analysis, May 26–27
Prof. Prasad Balkundi
Social networking is now a constant in our everyday lives and how it affects businesses and research has major implications. You will learn theoretical and methodological skills to independently conduct studies using social network analysis. Learn about network theories, their corresponding measures, and how to obtain data for network analysis. The training you will receive in social network analysis software (UCINET; NETDRAW) will enable you to learn analytic, empirical, and presentation options.
Session 4: Building a Better Regression Model, May 28–29
Prof. Christopher Dennison
Begin with an overview of regression models, focusing primarily on the interpretation of coefficients in multiple linear regression and then learn several analytic techniques to develop your skills. Specific topics will include testing coefficient differences within/across models, interaction terms, nonlinearity, and nonlinear interactions. You will finalize your training experience with an overview of dealing with missing data as well as regression models for count and categorical outcomes.