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.

Precision and accuracy are often incorrectly 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.

Measurements are said to have high-precision when there is little scatter.

### 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:

If you analyze these measurements, you will notice that they are not close to the target (10 meters) but are very close to one another. There is very little difference in their lengths, so their measurements have very little scatter.

In this case, the measurements are precise.

Precision is a measure of the variation among values.

### Accuracy

Accuracy 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.

### The Difference Between Accuracy and Precision

There are a few differences between accuracy and precision:

- Accurate data are close to the target value, while precise data are close to each other.
- Accuracy is always desired while precision is desirable when it is coupled with accuracy.
- Accurate data can be precise while precise data may or may not be accurate.
- Precision and accuracy are independent of each other.
- One measurement is enough for accuracy, while precision requires many measurements.

### 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 take corrective and preventive action.

### Summary

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 a PMP exam point 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

So clear.

Thanks, Subrata.

Excellent!

Thanks, Rachita.

If there is a toss up between precision and accuracy, which will be more important for measuring instrument?

Precision is useless with accuracy. We want product to be accurate.

Excellent explanation.

Thanks Hema for your comment.

Clearly described with examples, easy to understand. Thanks

You are welcome Harikrishnan.

Thank you for clarifying accurate and precise, this clears up all the confusion! Cheers to you!

You are welcome Linda.

Fahad, please explain accuracy and precision in terms of control chart also by giving an example. How values are scattered across mean and when should we say they are accurate and mean. And when the process has to be adjusted and when to be improved.

COntrol chart diagram link: http://www.oliverlehmann.com/contents/free-downloads/175_PMP_Sample_Questions.pdf

o The process has high precision but low accuracy. It should be adjusted.

o The process has high precision but low accuracy. It should be improved.

o The process has high accuracy but low precision. It should be adjusted.

o The process has high accuracy but low precision. It should be improved.

In future when I update this blog post, I’ll this information as well.

superb !!!!!

Thanks Vivek.

i loved this article. thank you

You are welcome Sakinah.

You are really good

🙂

Good stuff! thank you!!

You are welcome Bukola.

Very helpful indeed. You make these concepts and definitions very easy to understand.

God bless you.

Thanks NDEH for your comment.

Explanation is superb and easy to understand. My query, to calculate scatter, max value-min value of compared items. – is it correct?

You need to see the density of scatter.

excellent article!

Can you please also elaborate when should I improve my process and when should I adjust?

If the process is precise but not accurate you should adjust it but if the process is neither accurate nor precise you should improve it.

Thanks Fahad. Very good explanation and article.

You are welcome Shankar.

Very helpful! Thanks

You’re welcome Joy.

Good explanation Fahad Usman..thanks for it

You are welcome Tuba.

Thanks its very elaborated description

Thanks Atul for you comment.

Thanks , it was perfect description , I have been confused with this two 🙂

You’re welcome Maryam.

Thank Mukta for your visit.

thanks

Very clear. Wonderful.

Thanks for posting

You’re welcome Andres, and thanks for your visit.

Thanks for this wonderful website. My only suggestion is that you group all various under their respective Knowledge area so anytime we visit it will be easy to make reference. Million thanks

You can find it here:

https://pmstudycircle.com/archive/

Good examples and explanation, but can you please elaborate the below:

in your first example where results are 10.490, 10.495, 10.500…. can we say it is both accurate and precise as result is close to 10.

Similarly in the second example, 9.8, 9.9 and so on… can we still say it is precise and accurate??? as again values are less scattered (in the given sample) and close to 10?

Also, i will appreciate if you can clarify another question. (based on Oliver Lehmann’s questions)… Qs.9 from 175 questions http://www.oliverlehmann.com/contents/free-downloads/175_PMP_Sample_Questions.pdf

the options are “process should be adjusted” or improved… the correct answer goes with adjusted…

i want to know if there is any rule of when to adjust or improve? this is not clear at all and i can’t find any good reference 🙁

In my first example, all values are close to 10.5 meters means they are precise (note that, required length is 10.00 m). Though they are not close to the target length.

In second example, values are moving around 10.0 meters, meaning they are close to the target length but not very precise (they are not very close to each other).

Very nice post

its excellent article

Excellent post. Especially the pictorial representation.

Thanks for stopping by and liking my post.