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4 Tutorials that teach Accuracy and Precision in Measurements
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Accuracy and Precision in Measurements

Accuracy and Precision in Measurements

Author: Katherine Williams

Determine accuracy and precision in measurements.

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Video Transcription

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This tutorial covers accuracy and precision. Accuracy refers to our aim, how close we are to the desired target. We often use a bullseye in these sets of examples. So if you're very accurate, your shots are going to be very close to the center. They might not be all exactly on it, but they're going to be close to it. So this is what an accurate bullseye would look like.

If you're inaccurate, you're aiming towards the right spot, but you don't really get there very often. So your shots would be sprayed around center, something like this. They're all aiming towards the right place, but they don't end up getting there.

Now, another measurement that we talk about is precision. It's how close things are to each other, how much we're able to reproduce that measurement. So if something's precise, the shots are going to be clustered really close together. They're going to look like this. The shots are all really close to each other. It could be off to one side. They could be right around the center, as long as they're close to each other. Imprecision is when the shots are really spread apart. They're not near each other. You're not able to reduce your original shot really easily.

Accuracy and precision are independent of each other. So this means that you could have high precision and low accuracy. You could have low accuracy and high precision. You would have low of both. You could have high of both. We'll go through a chart see all these different examples.

This chart here shows all the possible combinations of accuracy and precision. We could have low accuracy or high accuracy. We could have low precision or high precision. So in this first box, we have low accuracy and low precision. The low accuracy means our shots aren't aiming towards the center. The low precision means that our shots aren't very close to each other. So it's something that might look like this. The shots aren't near the center, and they're not close to each other.

If we had the opposite situation, if we had high accuracy and high precision, the shots are going to be very close to each other and close to the center, something like that. If we get something in between, if we had high accuracy and low precision, high accuracy means we're aiming in the right spot. We're aiming towards the center. And then the low precision means the shots aren't all that close to each other, so it would look like that. If we had the opposite, if we had high precision but low accuracy, the low accuracy, our shots aren't in the right spot, but they're high precision means they're close together, something like that.

So when we're doing a study, we're trying to aim to have high accuracy and high precision. We want to be accurate. We want to be heading towards the right value. We want to be mimicking the population. But we also want to be precise. We want to be reproducible. We want our measurements to be close to each other.

So this is important distinction to make when you're disturbing whether or not your data is accurate. Sometime you might be confusing accuracy for precision, so it's important to distinguish between the two. Accuracy is your aim. Are you heading towards the right place with it? Precision is your reproduceability, how close the measurements are to each other. Thank you.

Terms to Know

The extent to which the values, when considered all together, center around the correct value for a variable.


The extent to which the values are very close to each other, even if they are not near the correct value.