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Jacqueline Woolley, Chair The University of Texas at Austin, SEA 4.212, Austin, TX 78712 • (512) 475-7596

John G Hixon

Lecturer Ph.D., University of Texas at Austin

John G Hixon

Contact

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.

Interests

Non-linear modeling and noise reduction in time-series analysis

PSY 384K • Adv Stats: Experimental Design

43890 • Spring 2011
Meets TTH 1230pm-200pm SEA 2.116
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Consideration of problems of analysis and design commonly encountered in psychological research. Three lecture hours a week for one semester. Prerequisite: Graduate standing, an undergraduate statistics course, and consent of instructor.

PSY 394T • Advanced Applied Statistics II

44010 • Spring 2011
Meets W 100pm-400pm SEA 2.116
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Seminars in Evolutionary Psychology. Three lecture hours a week for one semester. May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

PSY 394T • Advanced Applied Statistics I

43350 • Fall 2010
Meets W 900am-1200pm SEA 2.116
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Seminars in Evolutionary Psychology. Three lecture hours a week for one semester. May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

PSY 394T • Regression Analysis

43360 • Fall 2010
Meets TTH 330pm-500pm SEA 2.114
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Seminars in Evolutionary Psychology. Three lecture hours a week for one semester. May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

PSY 384K • Adv Stats: Experimental Design

44050 • Spring 2010
Meets TTH 1230pm-200pm SEA 2.116
show description

Consideration of problems of analysis and design commonly encountered in psychological research. Three lecture hours a week for one semester. Prerequisite:Graduate standing, an undergraduate statistics course, and consent of instructor.

PSY 394T • Advanced Applied Statistics II

44165 • Spring 2010
Meets W 100pm-400pm SEA 2.116
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Seminars in Evolutionary Psychology. Three lecture hours a week for one semester. May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

PSY 384M • Adv Statistics: Inferential

44240 • Fall 2009
Meets TTH 930-1100 SEA 2.108
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Same as Neuroscience 384M. Covers t-test, chi-square, analysis of variance, and nonparametric tests. Three lecture hours a week for one semester. Prerequisite: Graduate standing, an undergraduate statistics course, and consent of instructor.

PSY 394T • Advanced Applied Statistics I

44320 • Fall 2009
Meets W 900-1200 SEA 2.116
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Prerequisite: Graduate standing and consent of instructor.for one semester. May be repeated for credit when the topics vary.Seminars in Evolutionary Psychology. Three lecture hours a week

PSY 394T • Regression Analysis

44327 • Fall 2009
Meets TTH 330pm-500pm SEA 2.114
show description

Prerequisite: Graduate standing and consent of instructor.for one semester. May be repeated for credit when the topics vary.Seminars in Evolutionary Psychology. Three lecture hours a week

PSY 384K • Adv Stats: Experimental Design

43305 • Spring 2009
Meets TTH 1230pm-200pm SEA 2.116
show description

Consideration of problems of analysis and design commonly encountered in psychological research. Three lecture hours a week for one semester. Prerequisite:Graduate standing, an undergraduate statistics course, and consent of instructor.

PSY 394T • Advanced Applied Statistics II

43425 • Spring 2009
Meets W 1000-100pm SEA 2.114
show description

Seminars in Evolutionary Psychology. Three lecture hours a week for one semester. May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

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