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 Shen Xia, National "Thousand Talents Plan" Youth Project Lectures at DongFeng Forum of HUAT

Date:2018-03-29    Author:     Source:    ClickTimes:
 

On Tuesday evening, March 27th, Mr. Shen Xia, assistant professor and doctoral tutor of University of Edinburgh, also an young expert in the project of National "Thousand Talents Plan" Youth Project, was invited to give a lecture entitled Statistical Inference:  About the Specious Problems in a Mathematical Way. The lecture was presided by Mr. Wang shenghuai, professor and vice dean of mechanical school.


 

In the report, Mr. Shen took the controversial concept of P value in the theory of statistics as an example to elaborate the influence of multiple judgment on actual problems and then further discussed necessity of randomness and multiplicity over the development of matter with vivid examples. He also explained the contradiction between statistical inference and mathematical thinking, emphasizing the significance of correct ways of statistical thinking over people’s study, work and life. Instead of treating statistical problem in mathematical way, he encouraged people to learn to deal with the complex world constantly in a statistical way and no misleading would occur unless randomness was correctly understood.

 

After the report, Mr. Shen had discussion with teachers and students who are interested in probability inference.


 

Mr. Shen received his Ph.D. in bio-information from Uppsala University in Sweden in 2012. He is mainly engaged in the research of statistical methods in quantitative genetics. His research achievements are highly recognized by international experts in the field of statistical genetics. It has hosted and won many internationally competitive research funding support. In February 2018, he was selected by the project of Brain Gain Plan for Overseas Senior Talents advocated by the state. So far, he has published several papers in SCI, Nature Communication, American Journal of human Genetics, PloS genetics etc. His research field is highly interdisciplinary, which covers such areas as mathematical statistics, statistical calculation, large data processing, genetics and molecular biology.