<aside> 📖 The data-driven analytics lab is directed by Dr. Sunmee Kim, Assistant Professor of Quantitative Psychology at the University of Manitoba. Our goal is to develop and implement cutting-edge data analytics tools for data of diverse formats, structures, and scales, emerging from the social, behavioural, and health sciences.
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👋 Hi, I’m Sunmee. Data analytics in Psychology and related areas can be achieved through a variety of methods and techniques, such as statistical analysis, machine learning algorithms, and data visualization.
The key idea behind data-driven analytics is that data can offer a more meaningful and accurate basis for decision making compared to relying solely on human judgment. This opens up opportunities for novel and creative collaborative work with the researchers in substantive areas.
I’m using and studying a wide array of statistical methods and computational algorithms in the domains of multivariate statistics, predictive modeling, data reduction, non-parametric methods, regularization, and longitudinal data methods.
Starting from April 2023, I am appointed as a Research Affiliate at the Centre on Aging in the University of Manitoba. My research interests align with the Centre's focus, including: big data and predictive analytics for longitudinal data, data-driven approaches for identifying risk/protective factors associated with cognitive aging and late-life depression. See the attached poster for my presentation at the Centre on Aging Speaker Series
In my research, teaching, and student training, I predominantly use the R programming language due to my familiarity and proficiency with its capabilities. I’m also capable of employing other widely used statistical software (SAS, SPSS, Matlab, etc.) as needed. Explore my GitHub to explore my coding projects, particularly in R, including a package I've developed and various innovative methods.
The latest updates on ongoing laboratory activities for graduate and undergraduate students are shared and posted on the following page: Kim Quant Lab-Useful Recourses