Through this seminar, attendees will know when and how to use regression models for different data analysis tasks. Regression models are powerful tools for solving various problems in scientific analysis, and can be easily applied using R packages. Attendees will also learn some widely misused statistical models and how to avoid these misuses. The course require basic knowledge of statistics and R. There will be homework assignments each night to solidify the concepts from class. These are short and optional.
Linear regression advanced
Generalized linear regression, LASSO
Statistical rigor in biological analysis
Dr. Xinzhou Ge is a Postdoctoral Fellow in the Department of Computational Medicine with Prof. Jingyi Jessica Li. Arjun’s research focuses on enhancement of statistical rigor in biological data analysis and developing statistical and computational models. He received his BS in Statistics at Peking University and a PhD in Statistics at the University of California, Los Angeles.
Prerequisites: (W14) Intro to Modern Statistics with R
Length: 3 days, 2 hrs per day
Location: Boyer 529
Seats Available: 28
May 16, 17, and 18
1:30 PM – 4:30 PM
REGISTRATION IS OPEN!