Precision Versus Accuracy

Precision and accuracy are characteristics of measurement, which plays an important role in quality management. If the collected measurements do not meet the requirements, the deliverable cannot be accepted and is said to be of poor-quality.

You analyze the collected data for the accuracy and precision of the deliverable. If the measurements are accurate and precise, you will accept the deliverable. Otherwise, you will ask for corrective action.

A perfectly acceptable deliverable must be accurate and precise.

精密度和准确度往往错误地assumed to be synonyms of each other. Therefore, let me clarify our understanding of these quality management concepts.

Precision

Measurements are precise when the values of repeated measurements are clustered and have less scatter.

Precise measurements are not necessarily close to the target value, it just means that the results are close to one another. These measurements may or may not be near the target value.

据说，当散射量很小时，测量值是高精度的。

A Real-World Example of Precision

Assume that you received an order to supply 10,000 rods, 10 meters in length, to your client. You started production, and during the quality inspection, you randomly measure five rods.

The length of each rod is as follows:

如果您分析这些测量值，您会注意到它们不接近目标（10米），但彼此非常接近。它们的长度几乎没有差异，因此它们的测量值很小。

In this case, the measurements are precise.

Precision is a measure of the variation among values.

准确性

准确性is defined as how close the measured values are to the target value.

Scatter doesn’t have a significant role here. Accurate measurements may or may not be close to one another in a scatter. In other words, accurate data does not have to be precise, but it is ideal.

A Real-World Example of Accuracy

Let us consider the example discussed earlier. From a production lot, you randomly pick five rods for a quality inspection. You measure their lengths, and the dimensions are as follows:

You can see that all measurements are very close to the target length of the rod, which is 10 meters. Although, the values are closer to the target value, they are not close to each other and scatter is high.

So, you can say that these measurements are accurate but not precise.

You may be wondering which characteristic of measurement is more desirable.

The answer is “accuracy.”

This is because all data are close to the actual value, which is the sign of correctness of a deliverable. However, the best case is if the measurements are precise as well, because the measurements are close to the target value and very close to each other.

精度和精度之间的区别

精度和精度之间存在一些差异：

• Accurate data are close to the target value, while precise data are close to each other.
• 准确性is always desired while precision is desirable when it is coupled with accuracy.
• 准确的数据可以精确，而精确的数据可能准确或可能不准确。
• 精度和准确性彼此独立。
• 一种测量足以使其准确性，而精度需要许多测量。

The Significance of Accuracy and Precision

Measurements are important for quality management. If the measurements are precise as well as accurate, you can say that the product is defect free.

However, if the measured data is neither precise nor accurate, the product is defective; i.e. it is lacking correctness and exactness at the same time, and you have to takecorrective and preventive action.

概括

Precision and accuracy are vital quality management concepts. Accuracy is about closeness to the required value while precision measures repeatability. Precision alone is as important, unless it is coupled with accuracy. It is not necessary for precise measurements to be accurate or accurate measurements to be precise. Precise measurements can be accurate or inaccurate, and accurate measurements can be precise or imprecise.

It is the responsibility of the project management team to decide the level of accuracy and precision for their project deliverables during the quality inspection.

These topics are important from aPMP exampoint of view; therefore, you must know these concepts well and understand the differences between them.

I hope I have clarified a few things to you. If you have any thoughts or feedback, please share it through the comments section below.

Image credit =>NOAA’s National Ocean Service