Its sort of a joke, especially among industrial scientists, that physicists are ok at lots of things but not excellent at anything and that this explains why there are so few physicists in industry doing physics. While there is some accuracy to the joke, the truth is that the one thing that physicists excel at is measurement. As my graduate advisor used to point out, all of physics is counting. The trick is just to figure out the right things to count and the right way to count them. That’s the essence of measurement and its not always as easy as it seems.

Everybody needs to measure stuff. And whether you’re in a traditional business or a own a Web 2.0 startup or are just an average gal or guy, the need to measure things quickly and precisely has gotten a lot more intense in the past decade. You want to understand where your business is in the Long Tail or how “sticky” your website is or how much your coffee habit is costing you annually. And when I say precisely, I mean precisely in a, well, precise sense. To speak precisely, precise and accurate are not the same things. And this is the first thing to understand about measurement – a measurement is only valid when it is both sufficiently accurate and sufficiently precise.

**Accuracy vs. precision**

When you measure something accurately, your measurement gives you a number that is very close to the truth. You may not get the same number each time you make your measurement, but you know that its close to the actual value. When you measure something precisely, you’ll get close to the same result each time, but you may not be close to the actual answer. Ideally, we want our measurements to be both accurate and precise. In reality, most folks have a higher tolerance for lack of accuracy than they do for lack of precision. As long as the measurement is reasonably accurate, most people will settle for something that is off from the truth by a good bit so long as they get consistent answers from it. If you check your measuring cups in your kitchen drawers, you will find that they are pretty precise. Fill your 1/4 cup measure up 4 times and dump it in your 1 cup measure and it will fill it up exactly. (Or at least it did on each of the three sets of measures I had in my kitchen.) Yet, I have no idea – nor do I care – if the cups are calibrated properly. Do they deliver exactly 1 cup? If you care about that kind of accuracy, you’ll probably be using a graduated cylinder, not a plastic measuring cup. For most of us, the fact that the cups are precise is more important.

Does our tolerance for inaccuracy seem surprising? If you use Google Analytics to track your website stats, it shouldn’t be. Google can’t know, accurately, how many unique visitors actually visited your site. How can they? Even though they set a cookie to track your visitors, a lot of folks using Firefox will only accept cookies for that session, thus preventing Google from counting them over multiple visits. I do essentially the same thing with Omniweb. A lot of folks using IE will occasionally flush all of their cookies as a privacy measure. Each time the Google Analytics cookie for your site gets deleted, that user looks like a new user to Google. This means your unique visitor count is artificially high, as is your percentage of new users visiting your site. But, really, it doesn’t matter. You don’t care how accurate that number is, because whether you have 570 or 450 unique visitors per day isn’t as important as the trend. Is that number going up or down? Is it higher on Saturday mornings or weekday nights? As long as the measurement is precise, then those trends can be analyzed meaningfully.

Now we know what makes a measurement valid, and we understand that a large fraction of the time, we don’t need as much accuracy as we need precision. While I didn’t explicitly talk about it, it’s important to note that validity is predicated only upon *sufficient* accuracy and precision. Your car’s fuel gauge is neither terribly accurate nor terribly precise, but it represents a valid measurement because it gives you the data with sufficient accuracy and precision to keep you from running out of gas.

There are four other things to keep in mind about a measurement, which I’ll call the Four ‘R’s: Relevance, Range, Resolution, and Reproducibility.

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