Graduate Statistics Lab

Through a partnership with the College of Arts and Sciences (CAS) and the Graduate Student Association (GSA), all UB graduate students can receive free assistance with statistical aspects of their final projects (thesis, dissertation, qualifying paper/projects, course assignments). The lab caters to students with all levels of experience, even those with no stats background. Statistics workshops for students of all levels are also offered periodically.

The focus of this lab is to strengthen quantitative skills, so that the student can independently interpret and draw conclusions from their analysis. The lab will offer guidance on research projects by instructing students on principles of research design, teaching statistical concepts and procedures, and assist students with using/troubleshooting analytical software.

Registered graduate students can seek statistical support in 450 Park Hall at designated hours provided by the Statistics Lab Assistant during the academic year. 

Office Hours

Monday 3:00-5:00 p.m.
Thursday 2:00-4:00 p.m.
Friday 9:30-11:30 a.m.

For an initial consultation, please stop by office hours or schedule an appointment by contacting Jou Fei Huang via email at joufeihu@buffalo.edu.

Workshop learning materials

Assistance includes (but is not limited to):

Research Design

  • Technical aspects/principles of theory development and hypothesis testing
  • Experimental design
  • Survey design and sampling
  • Secondary data analysis

Quantitative Methods

  • Linear regression, logistic regression, and generalized logistic regression
  • Multilevel modeling
  • Structural equational modeling
  • Experimental methods and testing
  • Data mining/text analysis

Statistical Software and Programming

  • STATA, R, and SPSS.

Workshops

Getting Started with Stata for Statistics and data cleaning

Feb. 3, 2020  
3:30-5:00pm

Level: Beginners in quantitative studies.
This workshop introduces students to Stata and some useful commands for data cleaning. Topics include merging datasets, transform data, generate variables, etc.

Getting Started with R for Statistics

Feb. 11, 2020  
3:30-5:00pm

Level: Beginners in quantitative studies.
This workshop introduces students to R and RStudio. Topics include software download and installation, an overview of data structure and types of variables, useful resources for self-learning, and basic expressions and functions. 

Causal inference in R and SPSS: matching

Feb. 18, 2020
3:30-5:00pm

Level: Attendants should have some familiarity regarding and have a basic understanding of linear regression models and maximum likelihood estimation.
This workshop briefly covers the problem of using non-experimental data, and how we could increase the degree of representation of the sample by causal inference. I will mostly focus on how to conduct propensity matching and coarsened exact matching in R. In addition, a short demonstration in conducting propensity matching in SPSS is also provided.

Causal inference in Stata: instrumental variable method

March 4, 2020
3:30-5:00pm

Level: Attendants should have some familiarity regarding and have a basic understanding of linear regression models and maximum likelihood estimation.
Following the previous workshop, I am going to introduce another popular tactic in causal inference: the instrumental variable. This workshop briefly covers how to select the instrumental variable, and demonstrate how to conduct instrumental variable methods in Stata, and how to interpret the final result.