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Precision
Precision
Precision describes how close the measurements are to one another.
Precision is therefore a description of random errors, a helpful measure of statistical variability.
Associated with "reliability" or "trend."
Accuracy
Accuracy
Accuracy describes how close the measurements are to their true value.
Accuracy is therefore a description of human error, and may be a measure of a statistical bias, inadequate tools, or a central tendency.
Associated with "correctness" or "truth."
Low accuracy, low precision: in this case, the darts are very far away from each other, demonstrating low precision. They are also extremely far off from the bulls eye, so this is low in accuracy as well.
Data matching this model would be the least reliable and least true, and therefore the least helpful for analysis and comparison.
High accuracy, low precision: in this case, the darts are far away from each other, demonstrating low precision. However, the darts are fairly close to the bulls eye, so this would be high in accuracy.
Data matching this model is true and a reasonable average can be calculated despite the variability among the data points.
Low accuracy, high precision: in this case, the darts are very close to each other, demonstrating high precision. However, they are also extremely far off from the bulls eye, so this is low in accuracy.
Data matching this model is consistent but not necessarily true, which may indicate the need to re-calibrate equipment or revise the method.
High accuracy, high precision: in this case, the darts are very close to each other, demonstrating high precision. They are also right on target at the bulls eye, so they are high in accuracy.
Data matching this model is consistently true across trials and is therefore the most helpful for analysis and reproduction of the experiment.
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