Accuracy Vs. Precision
✔ The accuracy of a data set or a measuring instrument refers to the degree of uniformity of the observations around a desired value such that, on average, the target value is realized.
✔ The precision of a data set or a measuring instrument refers to the degree of variability of the observations.
✔ Accuracy is a measure of bias, whereas precision is a measure of spread.
✔ Analogy: The objective is to hit the target’s bull’s-eye, as shown in Fig.1.
- Fig.1 (a) shows a marksman who is precise and accurate. Each shot hits near or in the bull’s-eye (i.e., the marksman is accurate). The difference between successive shots is small (i.e., the marksman is precise).
- Fig.1 (b) shows a marksman who is accurate but not precise. If we average all his shots, the average would be close to the bull’s-eye. However, the difference between shots is very large.
- Fig.1(c) shows a marksman who is precise but not accurate. His average shot is not near the bull’s-eye. However, the difference between consecutive shots is very low.
Fig.1 Accuracy Vs Precision
- Fig.1(d) shows an example of a worksman who is neither accurate nor precise. There is no telling where the next shot will end up. He is off the bull’s-eye and the difference between shots is very large.
✔Therefore it is desirable to have a process that is both accurate and precise.