HSE 124 Advanced Biomedical Data Analysis
This course offers innovative and advanced methods and techniques for biomedical data analysis, often overlooked in the traditional training practices, such as graphics animation, spatial statistics and disease mapping via kernel density estimation, discriminant analysis, logistic regression, and PCA for binary classification via ROC curve and optimal threshold analysis, PCA-based objects/subjects ranking, optimal number of clusters, estimation of dose-response relationships in pharmacology and toxicology, tumor growth analysis, statistical identification of dugs’ synergy, nonlinear regression, D-value as an alternative to P-value, and others.
I follow the saying: “Examples are the expressway to knowledge.” We will be working with large and diverse real-life data sets such as the hotspot identification of the lung cancer rate in New Hampshire, the toenail arsenic distribution, TCGA gene clustering, prediction of the absolute marathon time world record, college student admission data, city crime, T-cell counts for COVID-19 diagnosis, underage drinking, correlation heatmap animation for stock prices and bones correlation in the Goldman osteometric dataset, nonparametric regression for Forbes Worlds’s biggest companies dataset, etc.
We will be using my book “Advanced Statistics with Applications in R” at www.eugened.org
(1 unit)
Instructor
Dr. Eugene Demidenko
Cross Listed Courses
QBS 124