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Related Concept Videos

Quality Control01:05

Quality Control

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Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
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Quality Assurance01:19

Quality Assurance

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Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
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Quality of Water01:19

Quality of Water

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In concrete preparation, the quality of water is paramount as it affects the strength and durability of the concrete. Potable water is usually preferred; however, it must not have excessive sodium or potassium to prevent compromising the concrete's integrity. Water quality is typically evaluated based on impurities such as dissolved solids, chlorides, and sulfates, and its pH value is ideally between 6 and 8. Even slightly acidic natural water may be acceptable unless it contains harmful...
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How Data are Classified: Categorical Data01:11

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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
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Pulse amplitude and quality01:17

Pulse amplitude and quality

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Pulse amplitude is a crucial indicator of cardiac health because it provides valuable insights into the strength of left ventricular contractions and the overall uniformity of blood circulation within the vasculature. The strength of the pulse is directly related to the force with which the heart contracts and the volume of blood being pumped.
A weak or absent pulse may indicate reduced cardiac output or poor left ventricular contraction, which can be signs of cardiovascular dysfunction or...
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How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
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Related Experiment Video

Updated: Feb 8, 2026

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI
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Improving the quality of XAFS data.

Hitoshi Abe1, Giuliana Aquilanti2, Roberto Boada3

  • 1High Energy Accelerator Research Organization (KEK), Tsukuba, Japan.

Journal of Synchrotron Radiation
|July 7, 2018
PubMed
Summary

This summary addresses quality assurance in X-ray Absorption Fine Structure (XAFS) spectroscopy experiments. It details common issues, limitations of related methods, and provides recommendations for improving XAFS data quality and reporting.

Keywords:
XAFSgood practice in XAFS experimentsharmonic rejection in XAFSquality of XAFS datasources of noise in XAFS

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Area of Science:

  • Materials Science
  • Spectroscopy
  • Analytical Chemistry

Background:

  • X-ray Absorption Fine Structure (XAFS) spectroscopy is a powerful technique for material characterization.
  • Ensuring high data quality in XAFS experiments is crucial for accurate analysis.
  • The Q2XAFS Workshop highlighted the need for standardized quality assurance practices.

Purpose of the Study:

  • To summarize discussions on factors affecting XAFS data quality.
  • To identify and address common problems in XAFS experiments.
  • To provide practical recommendations for improving XAFS data acquisition and reporting.

Main Methods:

  • Review of discussions from the Q2XAFS Workshop and Satellite to IUCr Congress 2017.
  • Identification of experimental challenges including noise, harmonic contamination, and monochromator issues.
  • Overview of limitations in related techniques like photon-out spectroscopies and energy-dispersive XAFS.

Main Results:

  • Detailed discussion of noise sources and minimization strategies in XAFS.
  • Analysis of challenges in advanced applications such as high-pressure and time-resolved operando catalyst studies.
  • Identification of pitfalls in data treatment, storage, and reporting.

Conclusions:

  • Adherence to good practices is essential for reliable XAFS results.
  • Understanding and mitigating experimental artifacts are key to data quality.
  • Standardized reporting of XAFS results will enhance reproducibility and comparability.