N = 1

We've all heard the saying, “If you don't learn from history, you're bound to repeat.” This post is all about learning from history. I was thinking of naming this post, “Live Experimentally.” But I really like the elegance of N=1. N=1 is about self-experimentation. Although, you can do what you want, I'm not really talking about, “Sex, Drugs and Rock 'n Roll.” I'm talking about everyday stuff. I'm talking about learning from our experiences so we can repeat the ones that work and fix the ones that don't.

Is it coincidental that the words “experience” and “experiment” are so similar? Definitely not. I saw an article, on the website of the Worcester Polytechnic Institute, that said, “An experiment is what you do to investigate something. It is the process by which you learn something … An experience is something that happens to you.” As you can see, the only really difference is the intent. If your goal is to learn something, you're leaning towards an experiment. If you're just coasting, and letting things happen, you're in the realm of experience. Both are useful. But, again, this post is about learning. So, we need to learn how to set up an experiment.

As you probably know, the letter N denotes the sample size in a scientific experiment. N=1 means a self-experiment. We most certainly cannot draw general conclusions from self-experimentation. However, we can definitely increase our effectiveness. The goal of N=1 is to become more effective. It's not to figure out some advice that we wish to impart on others. For the most part, you're probably going to want to keep your results to yourself. So, let's take a step back and review the scientific method.

I won't get real deep into it, let's just keep it simple. Science is fueled by curiosity. The first step is experience. Experience is an integral part of experimentation. Through our experiences, and observations, we wonder about the way the world works. We do a little bit of investigation so we can establish our viewpoint. This is our hypothesis. If we're smart, we test our hypothesis by running an experiment. Then we review the outcomes (the data) of our experiment to see if the hypothesis was wrong (you can never really prove that a hypothesis is “right.”)

If the hypothesis is proven to be incorrect, we throw it out and come up with a new one. That is to say, we come up with a new theory. Conversely, if the hypothesis is supported by the evidence, we want to tweak one variable and rerun the experiment. This is critically important. Ultimately what we looking for is something called the “mechanism.” I won't get into it other then to say that you want to change your variables one at a time. This will allow you to establish which is the key variable. What we're looking to do is distinguish between correlation and causation. Meaning, it decipher between what is cause versus what is merely connected.

This is something we all do rather intuitively. Let me give you an example. For the most part, people get sun-burned when it's warm outside. So, if we don't know how isolate our variables, we might think that warm weather causes the skin to burn. Of course, all we have to do is change one variable at a time to see if that hypothesis (warm weather burns) is accurate. A simple way of doing this would be to wear the same clothes, on a different warm day, and stay out of the sun. It doesn't take long to figure out that the sun is the culprit. The sun is the mechanism that burns skin. Had we put on a lot on clothing AND stayed out of the sun, we wouldn't know which is which. Changing two variables is of no help.

In the jargon of science, warm weather is correlated with burnt skin and the sun causes burnt skin. This is a distinction that messes a lot of people up. Of course, I intentionally used a very simple example to illustrate the point. We all know that warm weather doesn't cause sun-burns. You don't have to understand electromagnetic radiation to know that the light, coming from the sun, is what fries our skin. Incidentally, I am, in no way suggesting that you stay out of the sun. Sensible sun exposure is an important part of overall healthy living.

What I'm saying is to live experimentally. Practice is pretty much all that's required. With time, it becomes second nature to isolate your variables. Of course, sometimes changing one variable at a time is impossible. But there are all kinds of ways to construct personal experiments to figure out what's working, in our lives, and what's not.

I guess there's something of a paradox here. In science you generally want N to be as big a number as possible. In other words, you want as large a sample size as possible. Statistics teach us that the larger the sample size, the more reliable/accurate the data. However, if you know how to conduct proper experiments, and not be fooled by chance, you can get the best information from N=1. So, good luck and happy testing.