相关实验视频

Updated: Jan 15, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

8.7K

从套装插件到日常实践:在凝血分析中六西格玛和最大允许的不确定性

Coskun Cavusoglu1

  • 1Department of Medical Biochemistry, Umraniye Training and Research Hospital, Istanbul, Turkey.

Medicine
|October 7, 2025
PubMed
概括

这项研究评估了Sysmex CS-2500凝血分析仪.

关键词:
分析性能规范 (APS) 分析性能规范制造商数据 制造商数据最大允许的不确定性 (MAu)六西格玛公司的六西格玛

更多相关视频

Quantification of Heavy Metals and Other Inorganic Contaminants on the Productivity of Microalgae10:20

Quantification of Heavy Metals and Other Inorganic Contaminants on the Productivity of Microalgae

Published on: July 10, 2015

16.4K
Infinium Assay for Large-scale SNP Genotyping Applications13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

39.8K

相关概念视频

Data Validation01:15

Data Validation

Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
575
Uncertainty: Overview00:59

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
1.6K
Interpreting X̄ Charts01:13

Interpreting X̄ Charts

Interpreting x̄ charts, a type of control chart used in statistical process control helps monitor the variation in processes over time. The x̄ chart is based on the sample mean and allows for monitoring variations in the process mean over time. These charts are pivotal for quality assurance in manufacturing and other sectors.
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line...
297
Contaminants and Errors01:16

Contaminants and Errors

Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...
346
Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
50.1K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
99.7K