報告題目: Testing Multiple Hypothesis in
Big Data Analysis (大數(shù)據(jù)分析中的多元假設(shè)實驗)
報告人： Dr. Zhigen Zhao
報告內(nèi)容:
When testing one single hypothesis, it is given in every introduction statistics
textbook that one should reject the null hypothesis if the p-value is less than
or equal to alpha, a designated level reflecting one's willingness of
tolerating the type I error. In modern application, it is a common practice for
a scientist to test thousands, or even millions of hypothesis simultaneously.
Can we still use the simple rule stated earlier?
In this talk, I will present
the issue of the multiplicity when testing multiple hypothesis and the recent
development on this area in the last two decades. I will also discuss my recent
work on the construction of the optimal multiple testing procedures using the
decision empirical Bayes approach. I will highlight a few applications with big
data, arising from studies such as the genetics and social science.
時間：2015年6月29日上午 10:15--11:15
地點：犀浦校區(qū)2511
主講人簡介：Dr. Zhigen Zhao is an assistant professor at Department of Statistics, Temple University
(USA). He got his Ph.D. in mathematics from Cornell University in 2009.
主辦：研究生院
承辦：kaiyun開云官方網(wǎng)站
