John G Hixon
Assistant Professor of Instruction — Ph.D., University of Texas at Austin
Lecturer
Contact
- E-mail: hixon@austin.utexas.edu
- Phone: (512) 232-4633
- Office: SEA 2.206
Interests
Non-linear modeling and noise reduction in time-series analysis
Biography
I am a magna cum laude graduate of Case Western Reserve University, where in 1986 I received a B.A. with honors in economics. I received my Ph.D. from the University of Texas at Austin in 1991, concentrating in social psychology with a specialization (M.S. equivalent) in statistics. After serving on the faculty at the University of Connecticut, I went on to work with several governmental agencies, culminating in my service as Director of Quantitative Analysis for the Texas Department of Human Services from 1999-2003 and then as Senior Research Analyst for the Texas Legislative Council from early 2003 until I returned to the University of Texas in 2004. I currently teach four Ph.D.-level classes in statistical analysis at the University of Texas covering everything from basic approaches like analysis of variance and linear regression to advanced techniques like multivariate non-parametric modeling, simulation methods, structural equations, and more. My research focuses on nonlinear dynamic analysis systems, with primary applications in the investment and financial markets. In addition to my duties at the university, I serve as a statistical consultant to individuals, corporations, and government agencies.
I use statistical analysis literally every working day of my life and I have a deep appreciation for the power of properly deployed analysis to extract knowledge from data. Whether your ultimate aim is a career in academic research, government service, private industry, or practically anywhere else, knowledge of modern statistical analysis techniques will serve you well. The more training you have in these techniques, the more informed your understanding of others' research will be and, perhaps more importantly, the better able you will be to extract reliable and valid findings from your own data. I have often said to the students in my classes that the last 20 years or so have belonged to the people who have provided us with such incredible technological advances in our ability to collect and process data, but the next 20 years will belong to the folks who know how to extract knowledge from all of that data. That is what statistical analysis is all about. I truly enjoy teaching, my enthusiasm for the subject matter is probably evident, and I think all of this comes across in my classes.
Thank you for your interest. Via this page you can get some more details in the form of descriptions of my classes and the answers to some frequently asked questions. But don't hesitate to get in touch if I can be of any help.
