# Resources

Here you find a variety of resources related to my research and teaching.

## TutORial

I gave the TutORial "Approximations of Queueing Performance for Rapid Systems Design" at the 2015 INFORMS Annual Meeting. The abstract is: Recent advances in queueing analysis have yielded tractable approximations of performance metrics that can be used to quickly explore initial designs, to reduce computational burdens associated with simulation, or even to eliminate the need for simulation altogether. This TutORial takes you on an accessible tour of these recent methods, shows you how to apply them using numerical examples drawn from real applications, and discusses implementation challenges and potential opportunities. You can view the presentation here.

## Theme Park

I have developed the Theme Park computer game as an engaging motivation tool, geared towards the learning of probability and statistics for students in grades 9 through 12. As students analyze, maneuver, construct, and synthesize information throughout this game, they thoughtfully gain a deeper understanding of a variety of difficult topics in probability and statistics, while applying these concepts to a real-world situation. The game aligns with the Common Core Standards, and a teacher guide can be requested through the game's website.

## Fractional Brownian Motion

I maintain a website with resources related to simulation and estimation of a stochastic process known as fractional Brownian motion. It is nontrivial to simulate long-range dependent processes, and fractional Brownian motion in particular, and I wrote my masterâ€™s thesis on the subject in 2002. I have made lots of resources available.

## Lecture notes on stochastic processes and algorithms

On November 19-23, 2012, I gave ten lectures on stochastic processes and algorithms at the University of Wrocław, Poland. The lecture notes can be downloaded here. You may also be interested in this paper.

## Lecture in 3D

In my introductory probability classes, I do a lecture using 3-D glasses to explain the concept of joint distributions. Have a look at my page on joint probability mass functions and on joint probability density functions.