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Accuracy is how close your measured values are to the actual, correct value. Precision is how close your measured values are to each other. Your results in a lab are accurate if your data matches the actual value of whatever you measured. Your results are precise if the measurements in your different trials are close to each other and fall within the same range.
I liked the dartboard example that Dr. Lavelle used- in that higher accuracy would mean that the darts would hit the bullseye, and higher precision would mean that darts would hit the same spot (regardless of position) again and again.
Accuracy is how close you are to the true value, while precision is how consistent your results are in relation to each other. For example, you can keep getting similar results that are all far off from the true value (this is good precision with poor accuracy). Hope this helps!
Accuracy cares about how close a measurement taken is to some accepted, agreed upon value. Precision, however, refers to how reproducible a measurement is (in other words, when measuring something, do you get around the same value each time). Precision does not care about an accepted value for the item being measured.
Accuracy is the proximity of your value to the actual value. Precision is the closeness of all your values. Your value is more accurate if its closer to the actual value. Your values are precise if they're all relatively close to each other.
Accuracy reflects how close your measured values are to the true value, while precision reflects how close together your measurements were! Precision doesn't necessarily have to be close to the true value, just closely grouped together.
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