Quantum Football, Electron Preschoolers, and Schrodinger’s STEM


At this time of year as fans debate over the best players in college football, quantum mechanics combines with college sports to produce the Heisman uncertainty principal: you cannot know who has won the trophy until it is announced, and so you have to treat it as if every candidate has won and no candidates have won.**

What does the quantum theory of football have to do with a blog about learning SAS? Well, everyone around here is abuzz about Change the Equation and STEM (if you don’t know what this is, check it out and come back to me. It’s OK, I’ll wait for you.) Here is SAS’ contribution to their video contest:

The winner of the viral video contest is also in a quantum state of uncertainty until the contest ends and the winner is announced.

The SAS Training Post writers and all of the Education Division at SAS have reasons to be interested in motivating the next generation to study STEM—after all, they’re our future users!

But my interest in this topic goes further than that of a SAS instructor. The state of education is often on my mind as I consider the future my 1- and 4-year old knee-gnawers can look forward to. Schroediner’s quarterback aside, one thing that is certain: learning does not end with the school day. A well-rounded continuing education at home is part of the solution to the problem of lagging in math and science.

Last week, Michele Reister asked me to blog about how I ended up with a career in statistics. It’s certainly not where I thought I’d end up, trying to pick a major among theatre arts, psychology, English, physics, and computer science. There were dozens of influences that led ultimately to here and now, but one that makes my point about education is this: As strange as it is, I ended up in statistics partly thanks to William Shakespeare. Iambic pentameter fed a love for how numbers and patterns play into everyday life that later bloomed with academic research in human behavior. Sometimes I’d miss the whole point of a sonnet because the grammatical gymnastics producing the rhythm were so gorgeously executed. I wasn’t a very good actor, but I love a play on numbers.

Another influence was my freshman semester statistics professor at (what is now called) Texas State University. She nurtured our interest in statistics, focusing on the theoretical and applied aspects of statistics rather than on the calculations. We never had to memorize a formula. Competing with a fellow student for top score in the class, we both realized that data analysis, as it pertains to research in behavioral sciences, is far more interesting than anything else we might be doing. One thing leads to another, and we each ended up in a quantitative field (he is now on the faculty at Texas State). One topic informs another, and creativity grows from diversity of information.

To think of knowledge as a siloed system of isolated subjects-- math, English, history, physics—is to miss the joy of learning. Learning can be part of everyday life.

In teaching my 4-year old basic math concepts, we play games with the numbers. How many jelly beans do you have if I take 3 away from your handful of 12? What if you give 3 jelly beans to each of 4 kids? How many beans is that? She makes math part of her imaginative play, and it plants the seed of learning that will hopefully serve her for a lifetime.

And just like the quantum state of the Heisman, the quantum state of future STEM professionals requires that we treat it as if we are ahead—and behind—at the same time. Teaching math and science in ways that are fun, and that inform other areas of study, might be the key to motivating students to study STEM, so that future generations can “open the box” in 10 or 20 years to find a “living” in science, technology, engineering and math inside. Now I’m going to play catch in a probability field with my favorite (electron-speed) preschooler.

Thanks for reading!!

** with apologies to my dad, a retired physicist and fair-weather armchair quarterback, who is no doubt shaking his head right now.


About Author

Catherine Truxillo

Director of Analytical Education, SAS

Catherine Truxillo, Ph.D. has written or co-written SAS training courses for advanced statistical methods, including: multivariate statistics, linear and generalized linear mixed models, multilevel models, structural equation models, imputation methods for missing data, statistical process control, design and analysis of experiments, and cluster analysis. She also teaches SAS courses using SAS/IML®, SAS® Enterprise Guide®, SAS® Enterprise Miner™, SAS Forecast Studio and JMP® software. Before coming to SAS, Catherine completed her Ph.D. in Social Psychology with an emphasis in Statistics at The University of Texas at Austin. While at UT Austin, she completed an internship with the Math and Computer Science department's statistical consulting help desk and taught a number of undergraduate courses. While teaching and performing her own graduate research, she worked for a software usability design company conducting experiments to assess the ease-of-use of various software interfaces and website designs. Cat's personal interests include triathlon, hiking the woods near her home in North Carolina, and having tea parties with her two children.

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