Reviewed and Approved by Matt Traynor, PhD, Vice President, Innovation and Validation, Certified Laboratories
1-Minute Summary
- Measurement Uncertainty (MoU) explains why lab results are reported with a ± range — it’s a built-in measure of scientific confidence.
- Even validated methods involve natural variability from sampling, weighing, instruments, and analysts.
- MoU is essential when interpreting results against tight specifications for regulated products.
- Understanding uncertainty helps prevent unnecessary product rejections and supports smarter, risk-based decisions.
Why the ± Matters in Analytical Chemistry
Say you’re driving down the road and you glance at your speedometer: 30 mph, it reads. So, are you moving exactly 30 mph? Probably not. You could be going 29.5 mph or 30.8 mph. The point is, while your speedometer provides a close approximation of your speed, it’s not exact.
This variability is called Measurement Uncertainty (MoU), or sometimes Uncertainty of Measurement, and it’s inherent to every measurement we take, including those used in analytical chemistry. It’s the reason your Certificate of Analysis (COA) might show results like “8.4% ± 0.25%” instead of simply “8.4%”.
If you’ve ever wondered why labs don’t just report a single number instead of a range, this article is for you. We explain what Measurement Uncertainty in chemistry means, where it comes from, and how to use it when reviewing results.
What Is Measurement Uncertainty in Analytical Chemistry?
Measurement Uncertainty indicates how confident we can be in a reported value. It defines the range within which the true value is most likely to fall, given the unavoidable variability in sampling and testing.
Even the most accurate instruments and well-trained chemists encounter variability. Factors like sample variability, equipment calibration, and subtle differences in handling all contribute.
In fact, every ISO-accredited method must include an MoU. Without this range, a reported number lacks scientific context. It may appear more precise than it truly is, which could lead to incorrect decisions.
Which helps answer a common question…
“Why Not Just Report One Number?”
Because reporting a single value on a COA without a range suggests absolute certainty, and science doesn’t work that way.
All lab measurements involve some degree of variability. Presenting just one number, like 8.4%, gives the illusion of precision and overlooks the real-world complexities of analytical work.
By reporting 8.4% ± 0.25% or similar, the lab is saying: “This is our best estimate, and based on how the method performs, the true value is highly likely to fall within this range.”
This isn’t a flaw in the science, it’s an honest representation of what the data tell us. Measurement Uncertainty builds trust by transparently showing the level of confidence behind each result.
Where Does Measurement Uncertainty Come From?
Every step in analytical testing introduces variation. This is a natural part of working with real-world materials and instruments, not a sign of ineffectiveness on the part of the lab. These variations, though small, accumulate across the testing process.
Sources of Measurement Uncertainty include…
- Sample variability – The sample might not be perfectly mixed or homogeneous.
- Weighing – Even high-precision balances have measurement tolerances.
- Dilution and Preparation – Pipette calibration, human technique, and timing all affect results.
- Instrumentation – Instruments may drift slightly even within calibration standards.
- Analyst Technique – Subtle differences exist in handling, even among trained technicians.
Each of these sources contributes to the final uncertainty value. So, when you receive a result with a ± range, you’re seeing the result of a system designed to capture real-world variability.
Examples of Measurement of Uncertainty in Sample Types
Let’s look at two examples to illustrate how MoU plays out in real-world testing:
Zinc Oxide in an SPF Sunscreen
Say you’re measuring zinc oxide content in an SPF sunscreen product. Your internal specification is 8.2% to 8.6%.
Your COA comes back with a result of 8.4% ± 0.25%.
At first glance, that looks fine. But the ±0.25% tells us the true value could be as low as 8.15% or as high as 8.65%. That means part of the uncertainty range falls outside your specification.
So, does the sample fail?
Not necessarily. This is where understanding Measurement Uncertainty in chemistry becomes essential. In this case, the results are extremely close to your internal specification, and your team can use this information to make a confident, risk-based decision.
Protein in a Plant-Based Meat Alternative
Or, say you’re a food manufacturer claiming 20g of protein per serving on a plant-based burger.
The lab reports a result of 19.6g ± 0.6g.
The true protein content could range from 19.0g to 20.2g. Without the MoU, the 19.6g result might seem too low. But when you account for uncertainty, it’s within a reasonable range to support the label claim.
In both examples, MoU is a decision-making tool, not a nuisance.
Why Measurement Uncertainty Matters to You
Whether you work in cosmetics, food manufacturing, supplements, or another regulated industry, understanding Measurement Uncertainty helps you…
- Understand borderline results with clarity so you can make sound, risk-based decisions about your products.
- Set realistic internal specs that align with the capabilities of your test methods.
- Avoid unnecessary product rejections, which saves time and money.
If you’re consistently seeing results that just miss spec, the problem may not be the product, it could be that your specifications are tighter than the method’s known uncertainty.
How Do Labs Calculate Measurement Uncertainty?
Calculating MoU is a rigorous, data-driven process. At Certified Laboratories, we use the following procedure when validating a method:
- Test multiple replicates of the same sample, typically 12.
- Split replicates between two analysts, six by one technician, six by another.
- Perform statistical modeling to calculate standard deviation and apply confidence intervals.
The result is a ± value that reflects how much variation is expected when the method is applied to real samples.
For ISO-accredited methods, this range usually corresponds to a 95% confidence level, meaning we can be 95% certain the true value lies within the reported range.
MoU Means Confidence, Not Confusion
Measurement Uncertainty isn’t a disclaimer, it’s a declaration of scientific integrity.
It says, “We’ve measured this carefully, and here’s how confident we are in the result.” Without that ± value, you’re making decisions in the dark. With it, you gain insight, transparency, and reliability.
So, the next time your COA says 8.4% ± 0.25%, or similar, don’t just look at the number. Look at the whole picture.
If you need analytical chemistry testing for your samples, contact us and we’ll be happy to help.