where quantitative methods meet real-world phenomena

Statistics is more than just crunching numbers, it's about challenging assumptions, refining measurement, and building statistical tools that better capture the complexity of human behavior.

about the lab

Recently established at Claremont McKenna College, the STATS Lab explores and investigates how quantitative methods can help us understand real-world phenomena such as leadership, career development, and personality.

We’re interested in the messy, often nonlinear realities that statistics must navigate. Our work spans everything from simulation modeling to machine learning, always with an eye toward practical application.

research areas

  • We develop and refine psychological assessments to improve reliability, validity, and fairness. Our work includes forced-choice personality measures, response biases, and psychometric modeling using IRT and SEM.

  • We investigate how psychological tests and AI-driven models can reflect or amplify biases. Using DIF, test-taker reactions, and predictive bias testing, we ensure assessments are both scientifically valid and equitable.

  • We study how leadership is distributed, perceived, and assessed in organizations. Our work includes multilevel modeling, social network analysis, and longitudinal studies of leadership emergence and impact.

  • We apply GPT models, NLP, machine learning, and agent-based simulations to study human behavior in ways traditional methods cannot. These tools help us analyze text data, predict outcomes, and model complex systems.

  • We examine how people navigate careers, calling, and job transitions. Using longitudinal tracking, experience sampling, and text mining of job postings, we study early career experiences and long-term work outcomes.

  • We test whether psychological research is actually used in practice, analyzing how business leaders engage with academic findings. Our work includes meta-analyses, citation network studies, and science communication experiments.

Steven Zhou, PhD

Assistant Professor of Psychological Sciences

Dr. Steven Zhou is an incoming Assistant Professor of Psychological Sciences at Claremont McKenna College, specializing in psychometrics, quantitative methods, leadership, and career development. His research integrates machine learning, computational modeling, and advanced statistics to improve how we measure and understand human behavior. He has published over 20 peer-reviewed articles, secured almost $40k in external research funding, and actively works to bridge the scientist-practitioner gap in organizational psychology. Beyond academia, he has experience in HR, data analytics, and leadership development. As Director of the STATS Lab, he mentors students in cutting-edge methods, encouraging both rigor and creativity in psychological research.

welcome to STATS Lab

teaching

Take a look at the current and upcoming courses being taught by Dr. Zhou at Claremont McKenna College.

join us

Applications to join the lab will open in summer 2025.