Overview
Research in quantitative psychology and modelling emphasizes: 1) the development, evaluation, and application of statistical models; 2) advocating and demonstrating best practices and appropriate use of data-analytic techniques; and 3) use of computational models for explaining empirical results in psychology. This research is informed by and overlaps with advances in related disciplines such as statistics, biostatistics, psychometrics, machine learning, and natural language processing. Advancements in this field have wide-ranging impact across subdisciplines of psychology and other related social and natural science disciplines where human behaviour is studied.
Quantitative Psychology and Modelling at McGill
If you enjoy psychology and math/statistics or computer programming, have an interest in improving psychological research, or want to learn about how data science can be applied to the study of human behaviour, a career beginning with graduate studies in Quantitative Psychology and Modelling at McGill may be for you.
Click here to learn more about a PhD at McGill with a focus on Quantitative Psychology and Modelling.
To learn more about a career in Quantitative Psychology, follow the links below:
- American Psychological Association: Pursuing a Career in Quantitative Psychology - https://www.apa.org/education-career/guide/subfields/quantitative/education-training
- American Psychological Association: Career Spotlight - https://www.apa.org/ed/precollege/psn/2016/01/quantitative-psychology
Faculty
Core Faculty: