STAT 5301 Statistical Data Analysis

STAT 5301 provides students with practical experience in various statistical methods useful in modern biological data analysis including Linear and Logistic Regressions, Bootstrap Methods; Multivariate Data Reduction Techniques (Factor Analysis, Principal Component Analysis); Canonical Correspondence and Multidimensional scaling (MDS) analyses; Data Mining techniques including regression trees with Random Forest, K-means Clustering and Resampling Methods; and Introduction  to Bayesian Analysis. 

Credits

3

Schedule Type

Lecture

Grading Basis

Standard Letter (A-F)

Administrative Unit

School of Mathematical & Stat

Offered

As scheduled