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[RC] Empirical evidence versus statistics - Bruce Weary

I know, this sounds like it's about to get boring. But stay with me here. Science moves ahead slowly. Not so much because the scientific method is sluggish, but because the things we investigate have so many variables, known and unknown, that it takes a lot of time and effort to produce truly meaningful evidence. On the other hand, empirical evidence, by definition, is information derived by the trials and errors of experience. Most of you will probably agree that how you participate in endurance riding is largely based on your own empirical experience, and that which other riders have passed on to you, good or bad. We try different feeds, saddles, bits, workouts, electrolyte doses, recovery criteria, breeds of horse, etc.,.and produce outcomes. When we have a good outcome, we feel good about our methods. When we have a bad outcome, we go home and agonize over the variables, and wonder what to change for the better. Generally, we have a very high rate of completion and a very good safety record, nationwide, even with all these variables mixed in. How do we make sense of it all? Not through pure quantitative data. Gathering quantitative data involves recording the numbers of occurrences of a studied variable. The science of statistics is used to interpret that data, hopefully to some meaningful conclusion. The conclusions made are only as good as the data and the ability and indifference of the people interpreting them. A profit motivated drug company may make different conclusions about a drug study than the FDA would, for example.
Let's take a ridiculous example. John Crandall won the Tevis, the OD, and the National Championship rides this year, and took BC at all three. Statistically, he has a 100% success rate on those six criteria--winning and BC at each ride. Can we conclude that someone else should be able to get on that horse and produce the same results? In reality, if we were given that horse, all of us would probably still wonder how John pulled it off. What does he know that we don't know? What variables did he control that we aren't aware of? Someone else could try to win those rides and have a completely different result--like a dead horse. And there's the rub. Even if we had more quantitative data about our methods, what variables lurk behind them that we can't see, and complicate our ability to make decisions and set policy based on that set of data?
I'm embarrassed to admit this, but there are actually doctors in my profession (chiropractic) who align their treatment tables with true magnetic North before they treat a patient. When a patient improves, they feel that the alignment of the table had something to do with the patient's recovery. If 100% of the patients are treated this way, and 80% improve, what can we safely deduce?
Our rules and "long term philosophy" in this sport, I think, are predominantly based on our empirical experiences over the last 50 years, and influenced by veterinary insight/science. I think that in a small amateur sport such as ours, we are confined, for now, to making many of our policy decisions based largely on empirical experience, with experimental data playing a lesser role, due to it's scarcity and inherent variables. AERC has no professional statistician or clinical researchers on staff, that I know of.
We already have better than a 99.9% success rate as far as horses surviving rides. It's that last .1% we're working diligently to improve. Let's stay the course. No one is more angry and indignant than I am when a horse dies needlessly at one of our rides. But anger and indignance don't produce effective answers. We're "in business while under construction." And we're making progress.
There will be a quiz on this material tomorrow. Relax. It's open book. Prof. Q



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