### Archive for the ‘Measurement uncertainty’ Category

### A worked example of measurement uncertainty for a non-homogeneous population

A worked example of MU estimation on a non-homogeneous population

*For sampling a non-homogeneous target population such as grain cargo, grainy materials or soil, random positions may be selected and split duplicate samples are taken with duplicate laboratory analysis carried out on each sample received. This approach will be able to address both sampling and analytical uncertainties at the same time…..*

### A simple example of sampling uncertainty evaluation

A simple example of sampling uncertainty evaluation

In analytical chemistry, the test sample is usually only part of the system for which information is required. It is not possible to analyze numerous samples drawn from a population. Hence, one has to ensure a small number of samples taken are representative and assume that the results of the analysis can be taken as the answer for the whole…..

### The concept of measurement uncertainty – a new perspective

*Since the publication of the newly revised ISO/IEC 17025:2017, measurement uncertainty evaluation has expanded its coverage to include sampling uncertainty as well because ISO has recognized that sampling uncertainty can be a serious factor in the final test result obtained from a given sample ……*

### A linear regression approach to check bias between methods – Part II

**A Worked Example**

*Suppose that we determined the amount of uranium contents in 14 stream water samples by a well-established laboratory method and a newly-developed hand-held rapid field method…..*

A linear regression approach to bias between methods – Part II

### A linear regression approach to check bias between methods – Part I

*Linear regression is used to establish a relationship between two variables. In analytical chemistry, linear regression is commonly used in the construction of calibration curve for analytical instruments in, for example, gas and liquid chromatographic and many other spectrophotometric analyses….*

A linear regression approach to bias between methods – Part I

### Estimation of bias between two sampling methods

*Measurement uncertainty has two main contributors, namely sampling uncertainty and analytical uncertainty, but most laboratory analysts tend to equate analytical uncertainty as its measurement uncertainty based on the sample received. This may be true when the target (population) lot sampled is homogeneous where every part of the target have an equal chance of being incorporated in the sample…..*

Estimation of bias between 2 sampling methods

### A worked example to estimate sampling precision & measurement uncertainty

*Nearly all analysis requires the taking of a sample, a procedure which itself introduces uncertainty into the final test result. Hence a measurement uncertainty should cover both the uncertainties of sampling and analysis….*

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