5 Ways ATOMs are Like a Recipe

A recipe is a plan for cooking something–like the pizzookie pictured here.  I made six of them–three times I used the recipe to cook two at a time. Three times each one came out slightly different, but my last batch was the best. The recipe I used was just a guideline for combining ingredients, for temperature and duration to bake.

Experiments, whether they be in flight test or a wind tunnel, are kind of like that.  They vary slightly each time.

ATOMs are just a plan for how to combine the ingredients, guidelines for how to cook the data.  “Cooking the data” sounds bad, and it probably reinforces stereotypes we have about statistics and statisticians, but that’s not my intent.

What I hope to communicate is five very important facts about ATOMs.

  1. They help us transform the ingredients into something more appetizing.
  2. Even when you follow the recipe the same way each time, the results may vary slightly.
  3. If you leave out an ingredient, what you end up with will probably taste bad and look ugly.
  4. You should follow the recipe until you become a good cook, and then you can take some liberties.
  5. Until you’ve done it a lot, you probably don’t know how to tell when it’s done cooking.

On that last point–I mixed up the ingredients for the pizzookie, but I had to ask Beth for help on figuring out when it was done. You see, Beth has been cooking a lot longer than I have and has better judgment about these things.

And about that second to last point–a good cook is like a good leader–we need good leaders who know how to combine the ingredients. We need leaders who have expert judgment in a variety of things: measuring out the ingredients, knowing how long to mix, how hot to cook it, when to take it out of the oven, and most importantly, how to teach others how to cook. A leader with statistical judgment–that’s what I hope I can inspire you to be.

So let me ask you this: which analogy is more helpful–statistics as a see saw like last time or statistics as a recipe?

Where Do We Go From Here
How do we find our way then, when we are exploring the unknown, blazing a trail into uncharted territory? How do we apply elementary statistical principles to transform uncertainty into decisive action? What is to prevent us from making a preposterous application of ATOMs when we deal with very complex situations, those in which our intuition fails?

This question is not much different from that faced by Chuck Yeager before he ever broke the sound barrier or Neil Armstrong as he took that first step on the moon. Neither of these men, nor anyone around them–with hundreds or thousands of highly educated, very scientific people on these teams–none of these people knew what to expect. Or did they…?

ATOMs is a monthly column that introduces analytical tools of mathematics and statistics and illustrates their application. To read more about ATOMs, you can read Where Do We Go From Here, or view the online workbook here.

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