Short Courses
When: 12/14 (W), 9AM – 6PM, Location TBD
9:00 AM – 10:25 AM Short course: Lecture I
Title: Modern Statistical Process Control Chart and Their Applications to Big Data Analysis
Instructor: Prof. Qiu, Peihua (University of Florida)
10:35 AM – 12:00 PM Lecture II
Instructor: Prof. Qiu, Peihua (University of Florida)
12:00 PM – 1:30 PM Lunch
1:30 PM – 3:00 PM Lecture III
Instructor: Prof. Qiu, Peihua (University of Florida)
3:00 PM – 6:00 PM Computer Practice
Instructors: Prof. Jang, Dae-Heung and Prof. Noh, Maengseok (Pukyong National University)

Abstract
Title: Modern Statistical Process
Control Charts and Their Applications to Big Data Analysis
Instructor: Prof. Qui,
Peihua

Description:
Big data often take the form of data streams with observations of certain processes collected sequentially over time.
Among many different purposes, one common task to collect and analyze big data is to monitor the longitudinal performance/status of the related processes.
To this end, statistical process control (SPC) charts could be a useful tool, although conventional SPC charts need to be modified properly in some cases.
This short course discusses traditional SPC charts, including the Shewhart, CUSUM and EWMA charts, as well as some recent control charts based on change-point detection and fundamental multivariate SPC charts under the normality assumption.
It also introduces novel univariate and multivariate control charts for cases when the normality assumption is invalid and discusses control charts for profile monitoring.
Some examples will be discussed to use conventional control charts or their modifications for monitoring different types of processes with big data.
Among many potential applications, dynamic disease screening and profile/image monitoring will be discussed in some detail.


Textbook:
Qiu, P.
(2014), Introduction to Statistical Process Control, Boca Raton, FL: Chapman & Hall/CRC.
About the Instructor:
The instructor, Professor Peihua Qiu, is the current editor of Technometrics, a flagship journal in industrial statistics co-sponsored by ASA and ASQ.
He has been working on various statistical process control (SPC) problems since 1998, and has made substantial contributions in several SPC areas, including nonparametric SPC, SPC by change-point detection, and profile monitoring.
His recent book Qiu (2014, Chapman & Hall) gives a systematic description of both traditional and newer SPC methods.
Professor Qiu is an elected fellow of ASA and IMS, and an elected member of ISI.
After obtaining his Ph.D. in statistics from University of Wisconsin – Madison, he helped create the Biostatistics Center at the Ohio State University during 1996-1998. Then, he worked as an assistant (1998-2002), associate (2002-2007) and full professor (2007-2013) of the School of Statistics at the University of Minnesota.
He moved to the University of Florida as the founding chair of the Department of Biostatistics in 2013.
During his career, Professor Qiu is constantly involved in statistical consulting and collaborative research.